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Break
Sun Aug 6th 07:00 AM -- 06:00 PM @ Ground Level
Registration Desk
Break
Sun Aug 6th 08:15 -- 08:45 AM @ Gallery
Coffee Break
Tutorial
Sun Aug 6th 08:45 -- 11:00 AM @ Cockle Bay
Distributed Deep Learning with MxNet Gluon
Alex Smola · Aran Khanna
Tutorial
Sun Aug 6th 08:45 -- 11:00 AM @ Parkside 1
Interpretable Machine Learning
Been Kim · Finale Doshi-Velez
Tutorial
Sun Aug 6th 08:45 -- 11:00 AM @ Parkside 2
Machine Learning for Autonomous Vehicles
Raquel Urtasun · Andrew Gray · Carl Wellington
Break
Sun Aug 6th 11:00 -- 11:30 AM @ Gallery
Coffee Break
Break
Sun Aug 6th 11:00 AM -- 01:00 PM @ On your own
Lunch - on your own
Tutorial
Sun Aug 6th 01:00 -- 03:15 PM @ Cockle Bay
Recent Advances in Stochastic Convex and Non-Convex Optimization
Zeyuan Allen-Zhu
Tutorial
Sun Aug 6th 01:00 -- 03:15 PM @ Parkside 1
Deep Reinforcement Learning, Decision Making, and Control
Sergey Levine · Chelsea Finn
Tutorial
Sun Aug 6th 01:00 -- 03:15 PM @ Parkside 2
Deep Learning for Health Care Applications: Challenges and Solutions
Yan Liu · Jimeng Sun
Break
Sun Aug 6th 03:15 -- 03:45 PM @ Gallery
Coffee Break
Tutorial
Sun Aug 6th 03:45 -- 06:00 PM @ Cockle Bay
Real World Interactive Learning
Alekh Agarwal · John Langford
Tutorial
Sun Aug 6th 03:45 -- 06:00 PM @ Parkside 1
Sequence-To-Sequence Modeling with Neural Networks
Oriol Vinyals · Navdeep Jaitly
Tutorial
Sun Aug 6th 03:45 -- 06:00 PM @ Parkside 2
Robustness Meets Algorithms (and Vice-Versa)
Ankur Moitra
Break
Sun Aug 6th 06:15 -- 07:15 PM @ Ballroom
Opening Reception
Break
Mon Aug 7th 07:00 AM -- 06:30 PM @ Ground Level
Registration Desk
Break
Mon Aug 7th 08:15 -- 08:45 AM @ Gallery
Coffee Break
Break
Mon Aug 7th 08:45 -- 09:00 AM @ Darling Harbour Theatre
Opening Remarks
Invited Talk
Mon Aug 7th 09:00 -- 10:00 AM @ Darling Harbour Theatre
Causal Learning
Bernhard Schölkopf
Break
Mon Aug 7th 10:00 -- 11:00 AM @ The Press Room at the ICC
Press Conference
Break
Mon Aug 7th 10:00 -- 10:30 AM @ The Gallery
Coffee break
Talk
Mon Aug 7th 10:30 -- 10:48 AM @ Darling Harbour Theatre
Decoupled Neural Interfaces using Synthetic Gradients
Max Jaderberg · Wojciech Czarnecki · Simon Osindero · Oriol Vinyals · Alex Graves · David Silver · Koray Kavukcuoglu
Talk
Mon Aug 7th 10:30 -- 10:48 AM @ Parkside 1
PixelCNN Models with Auxiliary Variables for Natural Image Modeling
Alexander Kolesnikov · Christoph Lampert
Talk
Mon Aug 7th 10:30 -- 10:48 AM @ Parkside 2
Tight Bounds for Approximate Carathéodory and Beyond
Vahab Mirrokni · Renato Leme · Adrian Vladu · Sam Wong
Talk
Mon Aug 7th 10:30 -- 10:48 AM @ C4.5
Robust Adversarial Reinforcement Learning
Lerrel Pinto · James Davidson · Rahul Sukthankar · Abhinav Gupta
Talk
Mon Aug 7th 10:30 -- 10:48 AM @ C4.9& C4.10
Robust Probabilistic Modeling with Bayesian Data Reweighting
Yixin Wang · Alp Kucukelbir · David Blei
Talk
Mon Aug 7th 10:30 -- 10:48 AM @ C4.1
Multi-objective Bandits: Optimizing the Generalized Gini Index
Robert Busa-Fekete · Balazs Szorenyi · Paul Weng · Shie Mannor
Talk
Mon Aug 7th 10:30 -- 10:48 AM @ C4.4
Communication-efficient Algorithms for Distributed Stochastic Principal Component Analysis
Dan Garber · Ohad Shamir · Nati Srebro
Talk
Mon Aug 7th 10:30 -- 10:48 AM @ C4.8
The loss surface of deep and wide neural networks
Quynh Nguyen · Matthias Hein
Talk
Mon Aug 7th 10:30 -- 10:48 AM @ C4.6 & C4.7
Enumerating Distinct Decision Trees
Salvatore Ruggieri
Talk
Mon Aug 7th 10:48 -- 11:06 AM @ Darling Harbour Theatre
Understanding Synthetic Gradients and Decoupled Neural Interfaces
Wojciech Czarnecki · Grzegorz Świrszcz · Max Jaderberg · Simon Osindero · Oriol Vinyals · Koray Kavukcuoglu
Talk
Mon Aug 7th 10:48 -- 11:06 AM @ Parkside 1
Parallel Multiscale Autoregressive Density Estimation
Scott Reed · Aäron van den Oord · Nal Kalchbrenner · Sergio Gómez Colmenarejo · Ziyu Wang · Yutian Chen · Dan Belov · Nando de Freitas
Talk
Mon Aug 7th 10:48 -- 11:06 AM @ Parkside 2
Oracle Complexity of Second-Order Methods for Finite-Sum Problems
Yossi Arjevani · Ohad Shamir
Talk
Mon Aug 7th 10:48 -- 11:06 AM @ C4.5
Minimax Regret Bounds for Reinforcement Learning
Mohammad Gheshlaghi Azar · Ian Osband · Remi Munos
Talk
Mon Aug 7th 10:48 -- 11:06 AM @ C4.9& C4.10
Post-Inference Prior Swapping
William Neiswanger · Eric Xing
Talk
Mon Aug 7th 10:48 -- 11:06 AM @ C4.1
Online Learning with Local Permutations and Delayed Feedback
Liran Szlak · Ohad Shamir
Talk
Mon Aug 7th 10:48 -- 11:06 AM @ C4.4
SPLICE: Fully Tractable Hierarchical Extension of ICA with Pooling
Jun-ichiro Hirayama · Aapo Hyvärinen · Motoaki Kawanabe
Talk
Mon Aug 7th 10:48 -- 11:06 AM @ C4.8
Neural Taylor Approximations: Convergence and Exploration in Rectifier Networks
David Balduzzi · Brian McWilliams · Tony Butler-Yeoman
Talk
Mon Aug 7th 10:48 -- 11:06 AM @ C4.6 & C4.7
Simultaneous Learning of Trees and Representations for Extreme Classification and Density Estimation
Yacine Jernite · Anna Choromanska · David Sontag
Talk
Mon Aug 7th 11:06 -- 11:24 AM @ Darling Harbour Theatre
meProp: Sparsified Back Propagation for Accelerated Deep Learning with Reduced Overfitting
Xu SUN · Xuancheng REN · Shuming Ma · Houfeng Wang
Talk
Mon Aug 7th 11:06 -- 11:24 AM @ Parkside 1
Video Pixel Networks
Nal Kalchbrenner · Karen Simonyan · Aäron van den Oord · Ivo Danihelka · Oriol Vinyals · Alex Graves · Koray Kavukcuoglu
Talk
Mon Aug 7th 11:06 -- 11:24 AM @ Parkside 2
Global optimization of Lipschitz functions
Cédric Malherbe · Nicolas Vayatis
Talk
Mon Aug 7th 11:06 -- 11:24 AM @ C4.5
Fairness in Reinforcement Learning
Shahin Jabbari · Matthew Joseph · Michael Kearns · Jamie Morgenstern · Aaron Roth
Talk
Mon Aug 7th 11:06 -- 11:24 AM @ C4.9& C4.10
Evaluating Bayesian Models with Posterior Dispersion Indices
Alp Kucukelbir · Yixin Wang · David Blei
Talk
Mon Aug 7th 11:06 -- 11:24 AM @ C4.1
Model-Independent Online Learning for Influence Maximization
Sharan Vaswani · Branislav Kveton · Zheng Wen · Mohammad Ghavamzadeh · Laks V.S Lakshmanan · Mark Schmidt
Talk
Mon Aug 7th 11:06 -- 11:24 AM @ C4.4
Latent Feature Lasso
En-Hsu Yen · Wei-Chen Li · Sung-En Chang · Arun Suggala · Shou-De Lin · Pradeep Ravikumar
Talk
Mon Aug 7th 11:06 -- 11:24 AM @ C4.8
Sharp Minima Can Generalize For Deep Nets
Laurent Dinh · Razvan Pascanu · Samy Bengio · Yoshua Bengio
Talk
Mon Aug 7th 11:06 -- 11:24 AM @ C4.6 & C4.7
Resource-efficient Machine Learning in 2 KB RAM for the Internet of Things
Ashish Kumar · Saurabh Goyal · Manik Varma
Talk
Mon Aug 7th 11:24 -- 11:42 AM @ Darling Harbour Theatre
Learning Important Features Through Propagating Activation Differences
Avanti Shrikumar · Peyton Greenside · Anshul Kundaje
Talk
Mon Aug 7th 11:24 -- 11:42 AM @ Parkside 1
Adversarial Variational Bayes: Unifying Variational Autoencoders and Generative Adversarial Networks
Lars Mescheder · Sebastian Nowozin · Andreas Geiger
Talk
Mon Aug 7th 11:24 -- 11:42 AM @ Parkside 2
Strong NP-Hardness for Sparse Optimization with Concave Penalty Functions
Yichen Chen · Dongdong Ge · Mengdi Wang · Zizhuo Wang · Yinyu Ye · Hao Yin
Talk
Mon Aug 7th 11:24 -- 11:42 AM @ C4.5
Boosted Fitted Q-Iteration
Samuele Tosatto · Matteo Pirotta · Carlo D'Eramo · Marcello Restelli
Talk
Mon Aug 7th 11:24 -- 11:42 AM @ C4.9& C4.10
Automatic Discovery of the Statistical Types of Variables in a Dataset
Isabel Valera · Zoubin Ghahramani
Talk
Mon Aug 7th 11:24 -- 11:42 AM @ C4.1
Online Learning to Rank in Stochastic Click Models
Masrour Zoghi · Tomas Tunys · Mohammad Ghavamzadeh · Branislav Kveton · Csaba Szepesvari · Zheng Wen
Talk
Mon Aug 7th 11:24 -- 11:42 AM @ C4.4
Online Partial Least Square Optimization: Dropping Convexity for Better Efficiency and Scalability
Zhehui Chen · Lin Yang · Chris Junchi Li · Tuo Zhao
Talk
Mon Aug 7th 11:24 -- 11:42 AM @ C4.8
Geometry of Neural Network Loss Surfaces via Random Matrix Theory
Jeffrey Pennington · Yasaman Bahri
Talk
Mon Aug 7th 11:24 -- 11:42 AM @ C4.6 & C4.7
Multi-Class Optimal Margin Distribution Machine
Teng Zhang · Zhi-Hua Zhou
Talk
Mon Aug 7th 11:42 AM -- 12:00 PM @ Darling Harbour Theatre
Evaluating the Variance of Likelihood-Ratio Gradient Estimators
Seiya Tokui · Issei Sato
Talk
Mon Aug 7th 11:42 AM -- 12:00 PM @ Parkside 1
Learning Texture Manifolds with the Periodic Spatial GAN
Urs M Bergmann · Nikolay Jetchev · Roland Vollgraf
Talk
Mon Aug 7th 11:42 AM -- 12:00 PM @ Parkside 2
Stochastic Convex Optimization: Faster Local Growth Implies Faster Global Convergence
Yi Xu · Qihang Lin · Tianbao Yang
Talk
Mon Aug 7th 11:42 AM -- 12:00 PM @ C4.5
Why is Posterior Sampling Better than Optimism for Reinforcement Learning?
Ian Osband · Benjamin Van Roy
Talk
Mon Aug 7th 11:42 AM -- 12:00 PM @ C4.9& C4.10
Bayesian Models of Data Streams with Hierarchical Power Priors
Andres Masegosa · Thomas D. Nielsen · Helge Langseth · Dario Ramos-Lopez · Antonio Salmeron · Anders Madsen
Talk
Mon Aug 7th 11:42 AM -- 12:00 PM @ C4.1
The Sample Complexity of Online One-Class Collaborative Filtering
Reinhard Heckel · Kannan Ramchandran
Talk
Mon Aug 7th 11:42 AM -- 12:00 PM @ C4.8
The Shattered Gradients Problem: If resnets are the answer, then what is the question?
David Balduzzi · Marcus Frean · Wan-Duo Ma · Brian McWilliams · Lennox Leary · John Lewis
Talk
Mon Aug 7th 11:42 AM -- 12:00 PM @ C4.6 & C4.7
Kernelized Support Tensor Machines
Lifang He · Chun-Ta Lu · Guixiang Ma · Shen Wang · Linlin Shen · Philip Yu · Ann Ragin
Break
Mon Aug 7th 12:00 -- 01:30 PM @
Lunch - on your own
Talk
Mon Aug 7th 01:30 -- 01:48 PM @ Darling Harbour Theatre
Equivariance Through Parameter-Sharing
Siamak Ravanbakhsh · Jeff Schneider · Barnabás Póczos
Talk
Mon Aug 7th 01:30 -- 01:48 PM @ Parkside 1
Generalization and Equilibrium in Generative Adversarial Nets (GANs)
Sanjeev Arora · Rong Ge · Yingyu Liang · Tengyu Ma · Yi Zhang
Talk
Mon Aug 7th 01:30 -- 01:48 PM @ Parkside 2
GSOS: Gauss-Seidel Operator Splitting Algorithm for Multi-Term Nonsmooth Convex Composite Optimization
Li Shen · Wei Liu · Ganzhao Yuan · Shiqian Ma
Talk
Mon Aug 7th 01:30 -- 01:48 PM @ C4.5
Constrained Policy Optimization
Joshua Achiam · David Held · Aviv Tamar · Pieter Abbeel
Talk
Mon Aug 7th 01:30 -- 01:48 PM @ C4.9& C4.10
Ordinal Graphical Models: A Tale of Two Approaches
ARUN SAI SUGGALA · Eunho Yang · Pradeep Ravikumar
Talk
Mon Aug 7th 01:30 -- 01:48 PM @ C4.1
Efficient Regret Minimization in Non-Convex Games
Elad Hazan · Karan Singh · Cyril Zhang
Talk
Mon Aug 7th 01:30 -- 01:48 PM @ C4.4
Coresets for Vector Summarization with Applications to Network Graphs
Dan Feldman · Sedat Ozer · Daniela Rus
Talk
Mon Aug 7th 01:30 -- 01:48 PM @ C4.8
Recovery Guarantees for One-hidden-layer Neural Networks
Kai Zhong · Zhao Song · Prateek Jain · Peter Bartlett · Inderjit Dhillon
Talk
Mon Aug 7th 01:30 -- 01:48 PM @ C4.6 & C4.7
Dual Supervised Learning
Yingce Xia · Tao Qin · Wei Chen · Jiang Bian · Nenghai Yu · Tie-Yan Liu
Talk
Mon Aug 7th 01:48 -- 02:06 PM @ Darling Harbour Theatre
Warped Convolutions: Efficient Invariance to Spatial Transformations
Joao Henriques · Andrea Vedaldi
Talk
Mon Aug 7th 01:48 -- 02:06 PM @ Parkside 1
McGan: Mean and Covariance Feature Matching GAN
Youssef Mroueh · Tom Sercu · Vaibhava Goel
Talk
Mon Aug 7th 01:48 -- 02:06 PM @ Parkside 2
Breaking Locality Accelerates Block Gauss-Seidel
Stephen Tu · Shivaram Venkataraman · Ashia Wilson · Alex Gittens · Michael Jordan · Benjamin Recht
Talk
Mon Aug 7th 01:48 -- 02:06 PM @ C4.5
Reinforcement Learning with Deep Energy-Based Policies
Tuomas Haarnoja · Haoran Tang · Pieter Abbeel · Sergey Levine
Talk
Mon Aug 7th 01:48 -- 02:06 PM @ C4.9& C4.10
Scalable Bayesian Rule Lists
Hongyu Yang · Cynthia Rudin · Margo Seltzer
Talk
Mon Aug 7th 01:48 -- 02:06 PM @ C4.1
Identify the Nash Equilibrium in Static Games with Random Payoffs
Yichi Zhou · Jialian Li · Jun Zhu
Talk
Mon Aug 7th 01:48 -- 02:06 PM @ C4.4
Partitioned Tensor Factorizations for Learning Mixed Membership Models
Zilong Tan · Sayan Mukherjee
Talk
Mon Aug 7th 01:48 -- 02:06 PM @ C4.8
Failures of Gradient-Based Deep Learning
Shaked Shammah · Shai Shalev-Shwartz · Ohad Shamir
Talk
Mon Aug 7th 01:48 -- 02:06 PM @ C4.6 & C4.7
Learning Infinite Layer Networks without the Kernel Trick
Roi Livni · Daniel Carmon · Amir Globerson
Talk
Mon Aug 7th 02:06 -- 02:24 PM @ Darling Harbour Theatre
Graph-based Isometry Invariant Representation Learning
Renata Khasanova · Pascal Frossard
Talk
Mon Aug 7th 02:06 -- 02:24 PM @ Parkside 1
Conditional Image Synthesis with Auxiliary Classifier GANs
Augustus Odena · Christopher Olah · Jon Shlens
Talk
Mon Aug 7th 02:06 -- 02:24 PM @ Parkside 2
Stochastic DCA for the Large-sum of Non-convex Functions Problem and its Application to Group Variable Selection in Classification
Hoai An Le Thi · Hoai Minh Le · Duy Nhat Phan · Bach Tran
Talk
Mon Aug 7th 02:06 -- 02:24 PM @ C4.5
Prediction and Control with Temporal Segment Models
Nikhil Mishra · Pieter Abbeel · Igor Mordatch
Talk
Mon Aug 7th 02:06 -- 02:24 PM @ C4.9& C4.10
Learning Determinantal Point Processes with Moments and Cycles
John C Urschel · Ankur Moitra · Philippe Rigollet · Victor-Emmanuel Brunel
Talk
Mon Aug 7th 02:06 -- 02:24 PM @ C4.1
Follow the Compressed Leader: Faster Online Learning of Eigenvectors and Faster MMWU
Zeyuan Allen-Zhu · Yuanzhi Li
Talk
Mon Aug 7th 02:06 -- 02:24 PM @ C4.4
On Mixed Memberships and Symmetric Nonnegative Matrix Factorizations
Xueyu Mao · Purnamrita Sarkar · Deepayan Chakrabarti
Talk
Mon Aug 7th 02:06 -- 02:24 PM @ C4.8
Analytical Guarantees on Numerical Precision of Deep Neural Networks
Charbel Sakr · Yongjune Kim · Naresh Shanbhag
Talk
Mon Aug 7th 02:06 -- 02:24 PM @ C4.6 & C4.7
Random Fourier Features for Kernel Ridge Regression: Approximation Bounds and Statistical Guarantees
Haim Avron · Michael Kapralov · Cameron Musco · Christopher Musco · Ameya Velingker · Amir Zandieh
Talk
Mon Aug 7th 02:24 -- 02:42 PM @ Darling Harbour Theatre
Deriving Neural Architectures from Sequence and Graph Kernels
Tao Lei · Wengong Jin · Regina Barzilay · Tommi Jaakkola
Talk
Mon Aug 7th 02:24 -- 02:42 PM @ Parkside 1
Learning to Discover Cross-Domain Relations with Generative Adversarial Networks
Taeksoo Kim · Moonsu Cha · Hyunsoo Kim · Jungkwon Lee · Jiwon Kim
Talk
Mon Aug 7th 02:24 -- 02:42 PM @ Parkside 2
Gradient Projection Iterative Sketch for Large-Scale Constrained Least-Squares
Junqi Tang · Mohammad Golbabaee · Michael E Davies
Talk
Mon Aug 7th 02:24 -- 02:42 PM @ C4.5
An Alternative Softmax Operator for Reinforcement Learning
Kavosh Asadi · Michael L. Littman
Talk
Mon Aug 7th 02:24 -- 02:42 PM @ C4.9& C4.10
Deep Bayesian Active Learning with Image Data
Yarin Gal · Riashat Islam · Zoubin Ghahramani
Talk
Mon Aug 7th 02:24 -- 02:42 PM @ C4.1
On Kernelized Multi-armed Bandits
Sayak Ray Chowdhury · Aditya Gopalan
Talk
Mon Aug 7th 02:24 -- 02:42 PM @ C4.4
Nonnegative Matrix Factorization for Time Series Recovery From a Few Temporal Aggregates
Jiali Mei · Yohann De Castro · Yannig Goude · Georges Hébrail
Talk
Mon Aug 7th 02:24 -- 02:42 PM @ C4.8
Follow the Moving Leader in Deep Learning
Shuai Zheng · James Kwok
Talk
Mon Aug 7th 02:24 -- 02:42 PM @ C4.6 & C4.7
Logarithmic Time One-Against-Some
Hal Daumé · NIKOS KARAMPATZIAKIS · John Langford · Paul Mineiro
Talk
Mon Aug 7th 02:42 -- 03:00 PM @ Darling Harbour Theatre
Unsupervised Learning by Predicting Noise
Piotr Bojanowski · Armand Joulin
Talk
Mon Aug 7th 02:42 -- 03:00 PM @ Parkside 1
Wasserstein Generative Adversarial Networks
Martin Arjovsky · Soumith Chintala · Léon Bottou
Talk
Mon Aug 7th 02:42 -- 03:00 PM @ Parkside 2
Connected Subgraph Detection with Mirror Descent on SDPs
Cem Aksoylar · Orecchia Lorenzo · Venkatesh Saligrama
Talk
Mon Aug 7th 02:42 -- 03:00 PM @ C4.5
Fake News Mitigation via Point Process Based Intervention
Mehrdad Farajtabar · Jiachen Yang · Xiaojing Ye · Huan Xu · Rakshit Trivedi · Elias Khalil · Shuang Li · Le Song · Hongyuan Zha
Talk
Mon Aug 7th 02:42 -- 03:00 PM @ C4.9& C4.10
Bayesian Boolean Matrix Factorisation
Tammo Rukat · Christopher Holmes · Michalis Titsias · Christopher Yau
Talk
Mon Aug 7th 02:42 -- 03:00 PM @ C4.1
Second-Order Kernel Online Convex Optimization with Adaptive Sketching
Daniele Calandriello · Alessandro Lazaric · Michal Valko
Talk
Mon Aug 7th 02:42 -- 03:00 PM @ C4.4
Frame-based Data Factorizations
Sebastian Mair · Ahcène Boubekki · Ulf Brefeld
Talk
Mon Aug 7th 02:42 -- 03:00 PM @ C4.8
Theoretical Properties for Neural Networks with Weight Matrices of Low Displacement Rank
Liang Zhao · Siyu Liao · Yanzhi Wang · Zhe Li · Jian Tang · Bo Yuan
Talk
Mon Aug 7th 02:42 -- 03:00 PM @ C4.6 & C4.7
Understanding Black-box Predictions via Influence Functions
Pang Wei Koh · Percy Liang
Break
Mon Aug 7th 03:00 -- 03:30 PM @ The Gallery
Coffee Break
Talk
Mon Aug 7th 03:30 -- 03:48 PM @ Darling Harbour Theatre
Deep Transfer Learning with Joint Adaptation Networks
Mingsheng Long · Han Zhu · Jianmin Wang · Michael Jordan
Talk
Mon Aug 7th 03:30 -- 03:48 PM @ Parkside 1
Learning Hierarchical Features from Deep Generative Models
Shengjia Zhao · Jiaming Song · Stefano Ermon
Talk
Mon Aug 7th 03:30 -- 03:48 PM @ Parkside 2
Prox-PDA: The Proximal Primal-Dual Algorithm for Fast Distributed Nonconvex Optimization and Learning Over Networks
Mingyi Hong · Davood Hajinezhad · Ming-Min Zhao
Talk
Mon Aug 7th 03:30 -- 03:48 PM @ C4.5
Curiosity-driven Exploration by Self-supervised Prediction
Deepak Pathak · Pulkit Agrawal · Alexei Efros · Trevor Darrell
Talk
Mon Aug 7th 03:30 -- 03:48 PM @ C4.9& C4.10
Learning the Structure of Generative Models without Labeled Data
Stephen Bach · Bryan He · Alexander J Ratner · Christopher Re
Talk
Mon Aug 7th 03:30 -- 03:48 PM @ C4.1
Dueling Bandits with Weak Regret
Bangrui Chen · Peter Frazier
Talk
Mon Aug 7th 03:30 -- 03:48 PM @ C4.4
Nearly Optimal Robust Matrix Completion
Yeshwanth Cherapanamjeri · Prateek Jain · Kartik Gupta
Talk
Mon Aug 7th 03:30 -- 03:48 PM @ C4.8
Globally Optimal Gradient Descent for a ConvNet with Gaussian Inputs
Alon Brutzkus · Amir Globerson
Talk
Mon Aug 7th 03:30 -- 03:48 PM @ C4.6 & C4.7
Re-revisiting Learning on Hypergraphs: Confidence Interval and Subgradient Method
Chenzi Zhang · Shuguang Hu · Zhihao Gavin Tang · Hubert Chan
Talk
Mon Aug 7th 03:48 -- 04:06 PM @ Darling Harbour Theatre
Meta Networks
Tsendsuren Munkhdalai · Hong Yu
Talk
Mon Aug 7th 03:48 -- 04:06 PM @ Parkside 1
Bottleneck Conditional Density Estimation
Rui Shu · Hung Bui · Mohammad Ghavamzadeh
Talk
Mon Aug 7th 03:48 -- 04:06 PM @ Parkside 2
Exploiting Strong Convexity from Data with Primal-Dual First-Order Algorithms
Jialei Wang · Lin Xiao
Talk
Mon Aug 7th 03:48 -- 04:06 PM @ C4.5
Interactive Learning from Policy-Dependent Human Feedback
James MacGlashan · Mark Ho · Robert Loftin · Bei Peng · Guan Wang · David L Roberts · Matthew E. Taylor · Michael L. Littman
Talk
Mon Aug 7th 03:48 -- 04:06 PM @ C4.9& C4.10
Learning to Discover Sparse Graphical Models
Eugene Belilovsky · Kyle Kastner · Gael Varoquaux · Matthew B Blaschko
Talk
Mon Aug 7th 03:48 -- 04:06 PM @ C4.1
On Context-Dependent Clustering of Bandits
Claudio Gentile · Shuai Li · Purushottam Kar · Alexandros Karatzoglou · Giovanni Zappella · Evans Etrue Howard
Talk
Mon Aug 7th 03:48 -- 04:06 PM @ C4.4
Provable Alternating Gradient Descent for Non-negative Matrix Factorization with Strong Correlations
Yuanzhi Li · Yingyu Liang
Talk
Mon Aug 7th 03:48 -- 04:06 PM @ C4.8
Convexified Convolutional Neural Networks
Yuchen Zhang · Percy Liang · Martin Wainwright
Talk
Mon Aug 7th 03:48 -- 04:06 PM @ C4.6 & C4.7
Self-Paced Co-training
Fan Ma · Deyu Meng · Qi Xie · Zina Li · Xuanyi Dong
Talk
Mon Aug 7th 04:06 -- 04:24 PM @ Darling Harbour Theatre
SplitNet: Learning to Semantically Split Deep Networks for Parameter Reduction and Model Parallelization
Juyong Kim · Yookoon Park · Gunhee Kim · Sung Ju Hwang
Talk
Mon Aug 7th 04:06 -- 04:24 PM @ Parkside 1
Learning Deep Latent Gaussian Models with Markov Chain Monte Carlo
Matthew Hoffman
Talk
Mon Aug 7th 04:06 -- 04:24 PM @ Parkside 2
Doubly Greedy Primal-Dual Coordinate Descent for Sparse Empirical Risk Minimization
Qi Lei · En-Hsu Yen · Chao-Yuan Wu · Inderjit Dhillon · Pradeep Ravikumar
Talk
Mon Aug 7th 04:06 -- 04:24 PM @ C4.5
End-to-End Differentiable Adversarial Imitation Learning
Nir Baram · Oron Anschel · Itai Caspi · Shie Mannor
Talk
Mon Aug 7th 04:06 -- 04:24 PM @ C4.9& C4.10
Local-to-Global Bayesian Network Structure Learning
Tian Gao · Kshitij Fadnis · Murray Campbell
Talk
Mon Aug 7th 04:06 -- 04:24 PM @ C4.1
Provably Optimal Algorithms for Generalized Linear Contextual Bandits
Lihong Li · Yu Lu · Dengyong Zhou
Talk
Mon Aug 7th 04:06 -- 04:24 PM @ C4.4
No Spurious Local Minima in Nonconvex Low Rank Problems: A Unified Geometric Analysis
Rong Ge · Chi Jin · Yi Zheng
Talk
Mon Aug 7th 04:06 -- 04:24 PM @ C4.8
On the Expressive Power of Deep Neural Networks
Maithra Raghu · Ben Poole · Surya Ganguli · Jon Kleinberg · Jascha Sohl-Dickstein
Talk
Mon Aug 7th 04:06 -- 04:24 PM @ C4.6 & C4.7
Semi-Supervised Classification Based on Classification from Positive and Unlabeled Data
Tomoya Sakai · Marthinus C du Plessis · Gang Niu · Masashi Sugiyama
Talk
Mon Aug 7th 04:24 -- 04:42 PM @ Darling Harbour Theatre
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Chelsea Finn · Pieter Abbeel · Sergey Levine
Talk
Mon Aug 7th 04:24 -- 04:42 PM @ Parkside 1
Zero-Inflated Exponential Family Embeddings
Liping Liu · David Blei
Talk
Mon Aug 7th 04:24 -- 04:42 PM @ Parkside 2
A Richer Theory of Convex Constrained Optimization with Reduced Projections and Improved Rates
Tianbao Yang · Qihang Lin · Lijun Zhang
Talk
Mon Aug 7th 04:24 -- 04:42 PM @ C4.5
Learning in POMDPs with Monte Carlo Tree Search
Sammie Katt · Frans A Oliehoek · Chris Amato
Talk
Mon Aug 7th 04:24 -- 04:42 PM @ C4.9& C4.10
Composing Tree Graphical Models with Persistent Homology Features for Clustering Mixed-Type Data
XIUYAN NI · Novi Quadrianto · Yusu Wang · Chao Chen
Talk
Mon Aug 7th 04:24 -- 04:42 PM @ C4.1
Safety-Aware Algorithms for Adversarial Contextual Bandit
Wen Sun · Debadeepta Dey · Ashish Kapoor
Talk
Mon Aug 7th 04:24 -- 04:42 PM @ C4.4
Coherence Pursuit: Fast, Simple, and Robust Subspace Recovery
Mostafa Rahmani · George Atia
Talk
Mon Aug 7th 04:24 -- 04:42 PM @ C4.8
Depth-Width Tradeoffs in Approximating Natural Functions With Neural Networks
Itay Safran · Ohad Shamir
Talk
Mon Aug 7th 04:24 -- 04:42 PM @ C4.6 & C4.7
Iterative Machine Teaching
Weiyang Liu · Bo Dai · Ahmad Humayun · Charlene Tay · Chen Yu · Linda Smith · Jim Rehg · Le Song
Talk
Mon Aug 7th 04:42 -- 05:00 PM @ Darling Harbour Theatre
AdaNet: Adaptive Structural Learning of Artificial Neural Networks
Corinna Cortes · Xavi Gonzalvo · Vitaly Kuznetsov · Mehryar Mohri · Scott Yang
Talk
Mon Aug 7th 04:42 -- 05:00 PM @ Parkside 2
Convex Phase Retrieval without Lifting via PhaseMax
Tom Goldstein · Christoph Studer
Talk
Mon Aug 7th 04:42 -- 05:00 PM @ C4.5
DARLA: Improving Zero-Shot Transfer in Reinforcement Learning
Irina Higgins · Arka Pal · Andrei A Rusu · Loic Matthey · Christopher Burgess · Alexander Pritzel · Matthew Botvinick · Charles Blundell · Alexander Lerchner
Talk
Mon Aug 7th 04:42 -- 05:00 PM @ C4.9& C4.10
On Relaxing Determinism in Arithmetic Circuits
Arthur Choi · Adnan Darwiche
Talk
Mon Aug 7th 04:42 -- 05:00 PM @ C4.1
Adaptive Multiple-Arm Identification
Jiecao Chen · Xi Chen · Qin Zhang · Yuan Zhou
Talk
Mon Aug 7th 04:42 -- 05:00 PM @ C4.4
Tensor Decomposition with Smoothness
Masaaki Imaizumi · Kohei Hayashi
Talk
Mon Aug 7th 04:42 -- 05:00 PM @ C4.6 & C4.7
Automated Curriculum Learning for Neural Networks
Alex Graves · Marc Bellemare · Jacob Menick · Remi Munos · Koray Kavukcuoglu
Talk
Mon Aug 7th 05:15 -- 05:33 PM @ Darling Harbour Theatre
Learning to Learn without Gradient Descent by Gradient Descent
Yutian Chen · Matthew Hoffman · Sergio Gómez Colmenarejo · Misha Denil · Timothy Lillicrap · Matthew Botvinick · Nando de Freitas
Talk
Mon Aug 7th 05:15 -- 05:33 PM @ Parkside 1
Attentive Recurrent Comparators
Pranav Shyam · Shubham Gupta · Ambedkar Dukkipati
Talk
Mon Aug 7th 05:15 -- 05:33 PM @ Parkside 2
A Semismooth Newton Method for Fast, Generic Convex Programming
Alnur Ali · Eric Wong · Zico Kolter
Talk
Mon Aug 7th 05:15 -- 05:33 PM @ C4.5
Unifying task specification in reinforcement learning
Martha White
Talk
Mon Aug 7th 05:15 -- 05:33 PM @ C4.9& C4.10
An Infinite Hidden Markov Model With Similarity-Biased Transitions
Colin Dawson · Chaofan Huang · Clayton T. Morrison
Talk
Mon Aug 7th 05:15 -- 05:33 PM @ C4.1
Efficient Online Bandit Multiclass Learning with O(sqrt{T}) Regret
Alina Beygelzimer · Francesco Orabona · Chicheng Zhang
Talk
Mon Aug 7th 05:15 -- 05:33 PM @ C4.4
Orthogonalized ALS: A Theoretically Principled Tensor Decomposition Algorithm for Practical Use
Vatsal Sharan · Gregory Valiant
Talk
Mon Aug 7th 05:15 -- 05:33 PM @ C4.8
Efficient Nonmyopic Active Search
Shali Jiang · Luiz Gustavo Malkomes · Geoff Converse · Alyssa Shofner · Benjamin Moseley · Roman Garnett
Talk
Mon Aug 7th 05:15 -- 05:33 PM @ C4.6 & C4.7
Asymmetric Tri-training for Unsupervised Domain Adaptation
Kuniaki Saito · Yoshitaka Ushiku · Tatsuya Harada
Talk
Mon Aug 7th 05:33 -- 05:51 PM @ Darling Harbour Theatre
Learned Optimizers that Scale and Generalize
Olga Wichrowska · Niru Maheswaranathan · Matthew Hoffman · Sergio Gómez Colmenarejo · Misha Denil · Nando de Freitas · Jascha Sohl-Dickstein
Talk
Mon Aug 7th 05:33 -- 05:51 PM @ Parkside 1
State-Frequency Memory Recurrent Neural Networks
Hao Hu · Guo-Jun Qi
Talk
Mon Aug 7th 05:33 -- 05:51 PM @ Parkside 2
Approximate Newton Methods and Their Local Convergence
Haishan Ye · Luo Luo · Zhihua Zhang
Talk
Mon Aug 7th 05:33 -- 05:51 PM @ C4.5
A Distributional Perspective on Reinforcement Learning
Marc Bellemare · Will Dabney · Remi Munos
Talk
Mon Aug 7th 05:33 -- 05:51 PM @ C4.9& C4.10
Batched High-dimensional Bayesian Optimization via Structural Kernel Learning
Zi Wang · Chengtao Li · Stefanie Jegelka · Pushmeet Kohli
Talk
Mon Aug 7th 05:33 -- 05:51 PM @ C4.1
Active Learning for Accurate Estimation of Linear Models
Carlos Riquelme Ruiz · Mohammad Ghavamzadeh · Alessandro Lazaric
Talk
Mon Aug 7th 05:33 -- 05:51 PM @ C4.4
Tensor Decomposition via Simultaneous Power Iteration
Poan Wang · Chi-Jen Lu
Talk
Mon Aug 7th 05:33 -- 05:51 PM @ C4.8
Leveraging Union of Subspace Structure to Improve Constrained Clustering
John Lipor · Laura Balzano
Talk
Mon Aug 7th 05:33 -- 05:51 PM @ C4.6 & C4.7
Source-Target Similarity Modelings for Multi-Source Transfer Gaussian Process Regression
PENGFEI WEI · Ramon Sagarna · Yiping Ke · yEW ONG · CHI GOH
Talk
Mon Aug 7th 05:51 -- 06:09 PM @ Darling Harbour Theatre
Learning Gradient Descent: Better Generalization and Longer Horizons
Kaifeng Lv · Shunhua Jiang · Jian Li
Talk
Mon Aug 7th 05:51 -- 06:09 PM @ Parkside 1
Delta Networks for Optimized Recurrent Network Computation
Daniel Neil · Jun Lee · Tobi Delbruck · Shih-Chii Liu
Talk
Mon Aug 7th 05:51 -- 06:09 PM @ Parkside 2
Stochastic Adaptive Quasi-Newton Methods for Minimizing Expected Values
Chaoxu Zhou · Wenbo Gao · Donald Goldfarb
Talk
Mon Aug 7th 05:51 -- 06:09 PM @ C4.5
Hierarchy Through Composition with Multitask LMDPs
Andrew Saxe · Adam Earle · Benjamin Rosman
Talk
Mon Aug 7th 05:51 -- 06:09 PM @ C4.9& C4.10
From Patches to Images: A Nonparametric Generative Model
Geng Ji · Michael C. Hughes · Erik Sudderth
Talk
Mon Aug 7th 05:51 -- 06:09 PM @ C4.1
Adaptive Feature Selection: Computationally Efficient Online Sparse Linear Regression under RIP
Satyen Kale · Zohar Karnin · Tengyuan Liang · David Pal
Talk
Mon Aug 7th 05:51 -- 06:09 PM @ C4.4
A Unified Variance Reduction-Based Framework for Nonconvex Low-Rank Matrix Recovery
Lingxiao Wang · Xiao Zhang · Quanquan Gu
Talk
Mon Aug 7th 05:51 -- 06:09 PM @ C4.8
Active Heteroscedastic Regression
Kamalika Chaudhuri · Prateek Jain · Nagarajan Natarajan
Talk
Mon Aug 7th 05:51 -- 06:09 PM @ C4.6 & C4.7
Multi-task Learning with Labeled and Unlabeled Tasks
Anastasia Pentina · Christoph Lampert
Talk
Mon Aug 7th 06:09 -- 06:27 PM @ Darling Harbour Theatre
Learning Algorithms for Active Learning
Philip Bachman · Alessandro Sordoni · Adam Trischler
Talk
Mon Aug 7th 06:09 -- 06:27 PM @ Parkside 1
Recurrent Highway Networks
Julian Zilly · Rupesh Srivastava · Jan Koutnik · Jürgen Schmidhuber
Talk
Mon Aug 7th 06:09 -- 06:27 PM @ Parkside 2
Practical Gauss-Newton Optimisation for Deep Learning
Aleksandar Botev · Julian Hippolyt Ritter · David Barber
Talk
Mon Aug 7th 06:09 -- 06:27 PM @ C4.5
A Laplacian Framework for Option Discovery in Reinforcement Learning
Marlos C. Machado · Marc Bellemare · Michael Bowling
Talk
Mon Aug 7th 06:09 -- 06:27 PM @ C4.9& C4.10
Fast Bayesian Intensity Estimation for the Permanental Process
Christian Walder · Adrian N Bishop
Talk
Mon Aug 7th 06:09 -- 06:27 PM @ C4.1
Emulating the Expert: Inverse Optimization through Online Learning
Sebastian Pokutta · Andreas Bärmann · Oskar Schneider
Talk
Mon Aug 7th 06:09 -- 06:27 PM @ C4.4
An Efficient, Sparsity-Preserving, Online Algorithm for Low-Rank Approximation
David Anderson · Ming Gu
Talk
Mon Aug 7th 06:09 -- 06:27 PM @ C4.8
Active Learning for Cost-Sensitive Classification
Akshay Krishnamurthy · Alekh Agarwal · Tzu-Kuo Huang · Hal Daumé III · John Langford
Talk
Mon Aug 7th 06:09 -- 06:27 PM @ C4.6 & C4.7
Schema Networks: Zero-shot Transfer with a Generative Causal Model of Intuitive Physics
Ken Kansky · Thomas Silver · David A Mély · Mohamed Eldawy · Miguel Lazaro-Gredilla · Xinghua Lou · Nimrod Dorfman · Szymon Sidor · Scott Phoenix · Dileep George
Talk
Mon Aug 7th 06:27 -- 06:45 PM @ Parkside 2
Tensor Balancing on Statistical Manifold
Mahito Sugiyama · Hiroyuki Nakahara · Koji Tsuda
Talk
Mon Aug 7th 06:27 -- 06:45 PM @ C4.5
Modular Multitask Reinforcement Learning with Policy Sketches
Jacob Andreas · Dan Klein · Sergey Levine
Talk
Mon Aug 7th 06:27 -- 06:45 PM @ C4.9& C4.10
A Birth-Death Process for Feature Allocation
Konstantina Palla · David Knowles · Zoubin Ghahramani
Talk
Mon Aug 7th 06:27 -- 06:45 PM @ C4.1
Variants of RMSProp and Adagrad with Logarithmic Regret Bounds
Mahesh Chandra Mukkamala · Matthias Hein
Talk
Mon Aug 7th 06:27 -- 06:45 PM @ C4.4
Algorithms for $\ell_p$ Low-Rank Approximation
Flavio Chierichetti · Sreenivas Gollapudi · Ravi Kumar · Silvio Lattanzi · Rina Panigrahy · David Woodruff
Talk
Mon Aug 7th 06:27 -- 06:45 PM @ C4.8
Diameter-Based Active Learning
Christopher Tosh · Sanjoy Dasgupta
Talk
Mon Aug 7th 06:27 -- 06:45 PM @ C4.6 & C4.7
Risk Bounds for Transferring Representations With and Without Fine-Tuning
Daniel McNamara · Nina Balcan
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #1
Decoupled Neural Interfaces using Synthetic Gradients
Max Jaderberg · Wojciech Czarnecki · Simon Osindero · Oriol Vinyals · Alex Graves · David Silver · Koray Kavukcuoglu
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #2
PixelCNN Models with Auxiliary Variables for Natural Image Modeling
Alexander Kolesnikov · Christoph Lampert
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #3
Tight Bounds for Approximate Carathéodory and Beyond
Vahab Mirrokni · Renato Leme · Adrian Vladu · Sam Wong
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #4
Robust Adversarial Reinforcement Learning
Lerrel Pinto · James Davidson · Rahul Sukthankar · Abhinav Gupta
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #5
Robust Probabilistic Modeling with Bayesian Data Reweighting
Yixin Wang · Alp Kucukelbir · David Blei
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #6
Multi-objective Bandits: Optimizing the Generalized Gini Index
Robert Busa-Fekete · Balazs Szorenyi · Paul Weng · Shie Mannor
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #7
Communication-efficient Algorithms for Distributed Stochastic Principal Component Analysis
Dan Garber · Ohad Shamir · Nati Srebro
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #8
Enumerating Distinct Decision Trees
Salvatore Ruggieri
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #9
Understanding Synthetic Gradients and Decoupled Neural Interfaces
Wojciech Czarnecki · Grzegorz Świrszcz · Max Jaderberg · Simon Osindero · Oriol Vinyals · Koray Kavukcuoglu
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #10
Parallel Multiscale Autoregressive Density Estimation
Scott Reed · Aäron van den Oord · Nal Kalchbrenner · Sergio Gómez Colmenarejo · Ziyu Wang · Yutian Chen · Dan Belov · Nando de Freitas
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #11
Oracle Complexity of Second-Order Methods for Finite-Sum Problems
Yossi Arjevani · Ohad Shamir
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #12
Minimax Regret Bounds for Reinforcement Learning
Mohammad Gheshlaghi Azar · Ian Osband · Remi Munos
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #13
Post-Inference Prior Swapping
William Neiswanger · Eric Xing
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #14
Online Learning with Local Permutations and Delayed Feedback
Liran Szlak · Ohad Shamir
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #15
SPLICE: Fully Tractable Hierarchical Extension of ICA with Pooling
Jun-ichiro Hirayama · Aapo Hyvärinen · Motoaki Kawanabe
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #16
Simultaneous Learning of Trees and Representations for Extreme Classification and Density Estimation
Yacine Jernite · Anna Choromanska · David Sontag
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #17
meProp: Sparsified Back Propagation for Accelerated Deep Learning with Reduced Overfitting
Xu SUN · Xuancheng REN · Shuming Ma · Houfeng Wang
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #18
Video Pixel Networks
Nal Kalchbrenner · Karen Simonyan · Aäron van den Oord · Ivo Danihelka · Oriol Vinyals · Alex Graves · Koray Kavukcuoglu
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #19
Global optimization of Lipschitz functions
Cédric Malherbe · Nicolas Vayatis
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #20
Fairness in Reinforcement Learning
Shahin Jabbari · Matthew Joseph · Michael Kearns · Jamie Morgenstern · Aaron Roth
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #21
Evaluating Bayesian Models with Posterior Dispersion Indices
Alp Kucukelbir · Yixin Wang · David Blei
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #22
Model-Independent Online Learning for Influence Maximization
Sharan Vaswani · Branislav Kveton · Zheng Wen · Mohammad Ghavamzadeh · Laks V.S Lakshmanan · Mark Schmidt
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #23
Latent Feature Lasso
En-Hsu Yen · Wei-Chen Li · Sung-En Chang · Arun Suggala · Shou-De Lin · Pradeep Ravikumar
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #24
Resource-efficient Machine Learning in 2 KB RAM for the Internet of Things
Ashish Kumar · Saurabh Goyal · Manik Varma
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #25
Learning Important Features Through Propagating Activation Differences
Avanti Shrikumar · Peyton Greenside · Anshul Kundaje
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #26
Adversarial Variational Bayes: Unifying Variational Autoencoders and Generative Adversarial Networks
Lars Mescheder · Sebastian Nowozin · Andreas Geiger
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #27
Strong NP-Hardness for Sparse Optimization with Concave Penalty Functions
Yichen Chen · Dongdong Ge · Mengdi Wang · Zizhuo Wang · Yinyu Ye · Hao Yin
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #28
Boosted Fitted Q-Iteration
Samuele Tosatto · Matteo Pirotta · Carlo D'Eramo · Marcello Restelli
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #29
Automatic Discovery of the Statistical Types of Variables in a Dataset
Isabel Valera · Zoubin Ghahramani
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #30
Online Learning to Rank in Stochastic Click Models
Masrour Zoghi · Tomas Tunys · Mohammad Ghavamzadeh · Branislav Kveton · Csaba Szepesvari · Zheng Wen
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #31
Online Partial Least Square Optimization: Dropping Convexity for Better Efficiency and Scalability
Zhehui Chen · Lin Yang · Chris Junchi Li · Tuo Zhao
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #32
Multi-Class Optimal Margin Distribution Machine
Teng Zhang · Zhi-Hua Zhou
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #33
Evaluating the Variance of Likelihood-Ratio Gradient Estimators
Seiya Tokui · Issei Sato
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #34
Learning Texture Manifolds with the Periodic Spatial GAN
Urs M Bergmann · Nikolay Jetchev · Roland Vollgraf
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #35
Stochastic Convex Optimization: Faster Local Growth Implies Faster Global Convergence
Yi Xu · Qihang Lin · Tianbao Yang
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #36
Why is Posterior Sampling Better than Optimism for Reinforcement Learning?
Ian Osband · Benjamin Van Roy
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #37
Bayesian Models of Data Streams with Hierarchical Power Priors
Andres Masegosa · Thomas D. Nielsen · Helge Langseth · Dario Ramos-Lopez · Antonio Salmeron · Anders Madsen
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #38
The Sample Complexity of Online One-Class Collaborative Filtering
Reinhard Heckel · Kannan Ramchandran
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #39
Kernelized Support Tensor Machines
Lifang He · Chun-Ta Lu · Guixiang Ma · Shen Wang · Linlin Shen · Philip Yu · Ann Ragin
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #40
Equivariance Through Parameter-Sharing
Siamak Ravanbakhsh · Jeff Schneider · Barnabás Póczos
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #41
Generalization and Equilibrium in Generative Adversarial Nets (GANs)
Sanjeev Arora · Rong Ge · Yingyu Liang · Tengyu Ma · Yi Zhang
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #42
GSOS: Gauss-Seidel Operator Splitting Algorithm for Multi-Term Nonsmooth Convex Composite Optimization
Li Shen · Wei Liu · Ganzhao Yuan · Shiqian Ma
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #43
Constrained Policy Optimization
Joshua Achiam · David Held · Aviv Tamar · Pieter Abbeel
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #44
Ordinal Graphical Models: A Tale of Two Approaches
ARUN SAI SUGGALA · Eunho Yang · Pradeep Ravikumar
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #45
Efficient Regret Minimization in Non-Convex Games
Elad Hazan · Karan Singh · Cyril Zhang
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #46
Coresets for Vector Summarization with Applications to Network Graphs
Dan Feldman · Sedat Ozer · Daniela Rus
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #47
Recovery Guarantees for One-hidden-layer Neural Networks
Kai Zhong · Zhao Song · Prateek Jain · Peter Bartlett · Inderjit Dhillon
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #48
Dual Supervised Learning
Yingce Xia · Tao Qin · Wei Chen · Jiang Bian · Nenghai Yu · Tie-Yan Liu
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #49
Warped Convolutions: Efficient Invariance to Spatial Transformations
Joao Henriques · Andrea Vedaldi
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #50
McGan: Mean and Covariance Feature Matching GAN
Youssef Mroueh · Tom Sercu · Vaibhava Goel
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #51
Breaking Locality Accelerates Block Gauss-Seidel
Stephen Tu · Shivaram Venkataraman · Ashia Wilson · Alex Gittens · Michael Jordan · Benjamin Recht
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #52
Reinforcement Learning with Deep Energy-Based Policies
Tuomas Haarnoja · Haoran Tang · Pieter Abbeel · Sergey Levine
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #53
Scalable Bayesian Rule Lists
Hongyu Yang · Cynthia Rudin · Margo Seltzer
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #54
Identify the Nash Equilibrium in Static Games with Random Payoffs
Yichi Zhou · Jialian Li · Jun Zhu
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #55
Partitioned Tensor Factorizations for Learning Mixed Membership Models
Zilong Tan · Sayan Mukherjee
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #56
Failures of Gradient-Based Deep Learning
Shaked Shammah · Shai Shalev-Shwartz · Ohad Shamir
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #57
Learning Infinite Layer Networks without the Kernel Trick
Roi Livni · Daniel Carmon · Amir Globerson
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #58
Graph-based Isometry Invariant Representation Learning
Renata Khasanova · Pascal Frossard
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #59
Conditional Image Synthesis with Auxiliary Classifier GANs
Augustus Odena · Christopher Olah · Jon Shlens
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #60
Stochastic DCA for the Large-sum of Non-convex Functions Problem and its Application to Group Variable Selection in Classification
Hoai An Le Thi · Hoai Minh Le · Duy Nhat Phan · Bach Tran
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #61
Prediction and Control with Temporal Segment Models
Nikhil Mishra · Pieter Abbeel · Igor Mordatch
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #62
Learning Determinantal Point Processes with Moments and Cycles
John C Urschel · Ankur Moitra · Philippe Rigollet · Victor-Emmanuel Brunel
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #63
Follow the Compressed Leader: Faster Online Learning of Eigenvectors and Faster MMWU
Zeyuan Allen-Zhu · Yuanzhi Li
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #64
On Mixed Memberships and Symmetric Nonnegative Matrix Factorizations
Xueyu Mao · Purnamrita Sarkar · Deepayan Chakrabarti
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #65
Analytical Guarantees on Numerical Precision of Deep Neural Networks
Charbel Sakr · Yongjune Kim · Naresh Shanbhag
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #66
Random Fourier Features for Kernel Ridge Regression: Approximation Bounds and Statistical Guarantees
Haim Avron · Michael Kapralov · Cameron Musco · Christopher Musco · Ameya Velingker · Amir Zandieh
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #67
Deriving Neural Architectures from Sequence and Graph Kernels
Tao Lei · Wengong Jin · Regina Barzilay · Tommi Jaakkola
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #68
Learning to Discover Cross-Domain Relations with Generative Adversarial Networks
Taeksoo Kim · Moonsu Cha · Hyunsoo Kim · Jungkwon Lee · Jiwon Kim
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #69
Gradient Projection Iterative Sketch for Large-Scale Constrained Least-Squares
Junqi Tang · Mohammad Golbabaee · Michael E Davies
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #70
An Alternative Softmax Operator for Reinforcement Learning
Kavosh Asadi · Michael L. Littman
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #71
Deep Bayesian Active Learning with Image Data
Yarin Gal · Riashat Islam · Zoubin Ghahramani
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #72
On Kernelized Multi-armed Bandits
Sayak Ray Chowdhury · Aditya Gopalan
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #73
Nonnegative Matrix Factorization for Time Series Recovery From a Few Temporal Aggregates
Jiali Mei · Yohann De Castro · Yannig Goude · Georges Hébrail
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #74
Follow the Moving Leader in Deep Learning
Shuai Zheng · James Kwok
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #75
Logarithmic Time One-Against-Some
Hal Daumé · NIKOS KARAMPATZIAKIS · John Langford · Paul Mineiro
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #76
Unsupervised Learning by Predicting Noise
Piotr Bojanowski · Armand Joulin
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #77
Wasserstein Generative Adversarial Networks
Martin Arjovsky · Soumith Chintala · Léon Bottou
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #78
Connected Subgraph Detection with Mirror Descent on SDPs
Cem Aksoylar · Orecchia Lorenzo · Venkatesh Saligrama
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #79
Fake News Mitigation via Point Process Based Intervention
Mehrdad Farajtabar · Jiachen Yang · Xiaojing Ye · Huan Xu · Rakshit Trivedi · Elias Khalil · Shuang Li · Le Song · Hongyuan Zha
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #80
Bayesian Boolean Matrix Factorisation
Tammo Rukat · Christopher Holmes · Michalis Titsias · Christopher Yau
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #81
Second-Order Kernel Online Convex Optimization with Adaptive Sketching
Daniele Calandriello · Alessandro Lazaric · Michal Valko
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #82
Frame-based Data Factorizations
Sebastian Mair · Ahcène Boubekki · Ulf Brefeld
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #83
Theoretical Properties for Neural Networks with Weight Matrices of Low Displacement Rank
Liang Zhao · Siyu Liao · Yanzhi Wang · Zhe Li · Jian Tang · Bo Yuan
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #84
Understanding Black-box Predictions via Influence Functions
Pang Wei Koh · Percy Liang
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #85
Deep Transfer Learning with Joint Adaptation Networks
Mingsheng Long · Han Zhu · Jianmin Wang · Michael Jordan
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #86
Learning Hierarchical Features from Deep Generative Models
Shengjia Zhao · Jiaming Song · Stefano Ermon
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #87
Prox-PDA: The Proximal Primal-Dual Algorithm for Fast Distributed Nonconvex Optimization and Learning Over Networks
Mingyi Hong · Davood Hajinezhad · Ming-Min Zhao
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #88
Curiosity-driven Exploration by Self-supervised Prediction
Deepak Pathak · Pulkit Agrawal · Alexei Efros · Trevor Darrell
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #89
Learning the Structure of Generative Models without Labeled Data
Stephen Bach · Bryan He · Alexander J Ratner · Christopher Re
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #90
Dueling Bandits with Weak Regret
Bangrui Chen · Peter Frazier
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #91
Nearly Optimal Robust Matrix Completion
Yeshwanth Cherapanamjeri · Prateek Jain · Kartik Gupta
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #92
Globally Optimal Gradient Descent for a ConvNet with Gaussian Inputs
Alon Brutzkus · Amir Globerson
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #93
Re-revisiting Learning on Hypergraphs: Confidence Interval and Subgradient Method
Chenzi Zhang · Shuguang Hu · Zhihao Gavin Tang · Hubert Chan
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #94
Meta Networks
Tsendsuren Munkhdalai · Hong Yu
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #95
Bottleneck Conditional Density Estimation
Rui Shu · Hung Bui · Mohammad Ghavamzadeh
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #96
Exploiting Strong Convexity from Data with Primal-Dual First-Order Algorithms
Jialei Wang · Lin Xiao
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #97
Interactive Learning from Policy-Dependent Human Feedback
James MacGlashan · Mark Ho · Robert Loftin · Bei Peng · Guan Wang · David L Roberts · Matthew E. Taylor · Michael L. Littman
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #98
Learning to Discover Sparse Graphical Models
Eugene Belilovsky · Kyle Kastner · Gael Varoquaux · Matthew B Blaschko
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #99
On Context-Dependent Clustering of Bandits
Claudio Gentile · Shuai Li · Purushottam Kar · Alexandros Karatzoglou · Giovanni Zappella · Evans Etrue Howard
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #100
Provable Alternating Gradient Descent for Non-negative Matrix Factorization with Strong Correlations
Yuanzhi Li · Yingyu Liang
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #101
Convexified Convolutional Neural Networks
Yuchen Zhang · Percy Liang · Martin Wainwright
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #102
Self-Paced Co-training
Fan Ma · Deyu Meng · Qi Xie · Zina Li · Xuanyi Dong
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #103
SplitNet: Learning to Semantically Split Deep Networks for Parameter Reduction and Model Parallelization
Juyong Kim · Yookoon Park · Gunhee Kim · Sung Ju Hwang
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #104
Learning Deep Latent Gaussian Models with Markov Chain Monte Carlo
Matthew Hoffman
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #105
Doubly Greedy Primal-Dual Coordinate Descent for Sparse Empirical Risk Minimization
Qi Lei · En-Hsu Yen · Chao-Yuan Wu · Inderjit Dhillon · Pradeep Ravikumar
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #106
End-to-End Differentiable Adversarial Imitation Learning
Nir Baram · Oron Anschel · Itai Caspi · Shie Mannor
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #107
Local-to-Global Bayesian Network Structure Learning
Tian Gao · Kshitij Fadnis · Murray Campbell
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #108
Provably Optimal Algorithms for Generalized Linear Contextual Bandits
Lihong Li · Yu Lu · Dengyong Zhou
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #109
No Spurious Local Minima in Nonconvex Low Rank Problems: A Unified Geometric Analysis
Rong Ge · Chi Jin · Yi Zheng
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #110
On the Expressive Power of Deep Neural Networks
Maithra Raghu · Ben Poole · Surya Ganguli · Jon Kleinberg · Jascha Sohl-Dickstein
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #111
Semi-Supervised Classification Based on Classification from Positive and Unlabeled Data
Tomoya Sakai · Marthinus C du Plessis · Gang Niu · Masashi Sugiyama
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #112
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Chelsea Finn · Pieter Abbeel · Sergey Levine
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #113
Zero-Inflated Exponential Family Embeddings
Liping Liu · David Blei
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #114
A Richer Theory of Convex Constrained Optimization with Reduced Projections and Improved Rates
Tianbao Yang · Qihang Lin · Lijun Zhang
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #115
Learning in POMDPs with Monte Carlo Tree Search
Sammie Katt · Frans A Oliehoek · Chris Amato
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #116
Composing Tree Graphical Models with Persistent Homology Features for Clustering Mixed-Type Data
XIUYAN NI · Novi Quadrianto · Yusu Wang · Chao Chen
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #117
Safety-Aware Algorithms for Adversarial Contextual Bandit
Wen Sun · Debadeepta Dey · Ashish Kapoor
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #118
Coherence Pursuit: Fast, Simple, and Robust Subspace Recovery
Mostafa Rahmani · George Atia
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #119
Depth-Width Tradeoffs in Approximating Natural Functions With Neural Networks
Itay Safran · Ohad Shamir
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #120
Iterative Machine Teaching
Weiyang Liu · Bo Dai · Ahmad Humayun · Charlene Tay · Chen Yu · Linda Smith · Jim Rehg · Le Song
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #121
AdaNet: Adaptive Structural Learning of Artificial Neural Networks
Corinna Cortes · Xavi Gonzalvo · Vitaly Kuznetsov · Mehryar Mohri · Scott Yang
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #122
Convex Phase Retrieval without Lifting via PhaseMax
Tom Goldstein · Christoph Studer
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #123
DARLA: Improving Zero-Shot Transfer in Reinforcement Learning
Irina Higgins · Arka Pal · Andrei A Rusu · Loic Matthey · Christopher Burgess · Alexander Pritzel · Matthew Botvinick · Charles Blundell · Alexander Lerchner
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #124
On Relaxing Determinism in Arithmetic Circuits
Arthur Choi · Adnan Darwiche
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #125
Adaptive Multiple-Arm Identification
Jiecao Chen · Xi Chen · Qin Zhang · Yuan Zhou
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #126
Tensor Decomposition with Smoothness
Masaaki Imaizumi · Kohei Hayashi
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #127
Automated Curriculum Learning for Neural Networks
Alex Graves · Marc Bellemare · Jacob Menick · Remi Munos · Koray Kavukcuoglu
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #128
Attentive Recurrent Comparators
Pranav Shyam · Shubham Gupta · Ambedkar Dukkipati
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #129
An Infinite Hidden Markov Model With Similarity-Biased Transitions
Colin Dawson · Chaofan Huang · Clayton T. Morrison
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #130
Efficient Nonmyopic Active Search
Shali Jiang · Luiz Gustavo Malkomes · Geoff Converse · Alyssa Shofner · Benjamin Moseley · Roman Garnett
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #131
Asymmetric Tri-training for Unsupervised Domain Adaptation
Kuniaki Saito · Yoshitaka Ushiku · Tatsuya Harada
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #132
State-Frequency Memory Recurrent Neural Networks
Hao Hu · Guo-Jun Qi
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #133
Batched High-dimensional Bayesian Optimization via Structural Kernel Learning
Zi Wang · Chengtao Li · Stefanie Jegelka · Pushmeet Kohli
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #134
Leveraging Union of Subspace Structure to Improve Constrained Clustering
John Lipor · Laura Balzano
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #135
Source-Target Similarity Modelings for Multi-Source Transfer Gaussian Process Regression
PENGFEI WEI · Ramon Sagarna · Yiping Ke · yEW ONG · CHI GOH
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #136
Delta Networks for Optimized Recurrent Network Computation
Daniel Neil · Jun Lee · Tobi Delbruck · Shih-Chii Liu
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #137
From Patches to Images: A Nonparametric Generative Model
Geng Ji · Michael C. Hughes · Erik Sudderth
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #138
Active Heteroscedastic Regression
Kamalika Chaudhuri · Prateek Jain · Nagarajan Natarajan
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #139
Multi-task Learning with Labeled and Unlabeled Tasks
Anastasia Pentina · Christoph Lampert
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #140
Recurrent Highway Networks
Julian Zilly · Rupesh Srivastava · Jan Koutnik · Jürgen Schmidhuber
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #141
Fast Bayesian Intensity Estimation for the Permanental Process
Christian Walder · Adrian N Bishop
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #142
Active Learning for Cost-Sensitive Classification
Akshay Krishnamurthy · Alekh Agarwal · Tzu-Kuo Huang · Hal Daumé III · John Langford
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #143
Schema Networks: Zero-shot Transfer with a Generative Causal Model of Intuitive Physics
Ken Kansky · Thomas Silver · David A Mély · Mohamed Eldawy · Miguel Lazaro-Gredilla · Xinghua Lou · Nimrod Dorfman · Szymon Sidor · Scott Phoenix · Dileep George
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #144
A Birth-Death Process for Feature Allocation
Konstantina Palla · David Knowles · Zoubin Ghahramani
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #145
Diameter-Based Active Learning
Christopher Tosh · Sanjoy Dasgupta
Poster
Mon Aug 7th 06:30 -- 10:00 PM @ Gallery #146
Risk Bounds for Transferring Representations With and Without Fine-Tuning
Daniel McNamara · Nina Balcan
Break
Mon Aug 7th 06:45 -- 07:00 PM @ Gallery
Light snack
Break
Tue Aug 8th 07:00 AM -- 06:00 PM @ Ground Level
Registration Desk
Break
Tue Aug 8th 08:15 -- 09:00 AM @ Gallery
Coffee Break
Talk
Tue Aug 8th 09:00 -- 10:00 AM @ Darling Harbour Theatre
Test of Time Award
Break
Tue Aug 8th 10:00 -- 10:30 AM @ The Gallery
Coffee Break
Talk
Tue Aug 8th 10:30 -- 10:48 AM @ Darling Harbour Theatre
Relative Fisher Information and Natural Gradient for Learning Large Modular Models
Ke Sun · Frank Nielsen
Talk
Tue Aug 8th 10:30 -- 10:48 AM @ Parkside 1
Efficient Orthogonal Parametrisation of Recurrent Neural Networks Using Householder Reflections
zakaria mhammedi · Andrew Hellicar · James Bailey · Ashfaqur Rahman
Talk
Tue Aug 8th 10:30 -- 10:48 AM @ Parkside 2
Lazifying Conditional Gradient Algorithms
Gábor Braun · Sebastian Pokutta · Daniel Zink
Talk
Tue Aug 8th 10:30 -- 10:48 AM @ C4.5
Data-Efficient Policy Evaluation Through Behavior Policy Search
Josiah Hanna · Philip S. Thomas · Peter Stone · Scott Niekum
Talk
Tue Aug 8th 10:30 -- 10:48 AM @ C4.9& C4.10
Exact MAP Inference by Avoiding Fractional Vertices
Erik Lindgren · Alexandros Dimakis · Adam Klivans
Talk
Tue Aug 8th 10:30 -- 10:48 AM @ C4.1
Leveraging Node Attributes for Incomplete Relational Data
He Zhao · Lan Du · Wray Buntine
Talk
Tue Aug 8th 10:30 -- 10:48 AM @ C4.4
How Close Are the Eigenvectors of the Sample and Actual Covariance Matrices?
Andreas Loukas
Talk
Tue Aug 8th 10:30 -- 10:48 AM @ C4.8
Sketched Ridge Regression: Optimization Perspective, Statistical Perspective, and Model Averaging
Shusen Wang · Alex Gittens · Michael Mahoney
Talk
Tue Aug 8th 10:30 -- 10:48 AM @ C4.6 & C4.7
Distributed and Provably Good Seedings for k-Means in Constant Rounds
Olivier Bachem · Mario Lucic · Andreas Krause
Talk
Tue Aug 8th 10:48 -- 11:06 AM @ Darling Harbour Theatre
Learning Deep Architectures via Generalized Whitened Neural Networks
Ping Luo
Talk
Tue Aug 8th 10:48 -- 11:06 AM @ Parkside 1
On orthogonality and learning RNNs with long term dependencies
Eugene Vorontsov · Chiheb Trabelsi · Christopher Pal · Samuel Kadoury
Talk
Tue Aug 8th 10:48 -- 11:06 AM @ Parkside 2
Conditional Accelerated Lazy Stochastic Gradient Descent
Guanghui · Sebastian Pokutta · Yi Zhou · Daniel Zink
Talk
Tue Aug 8th 10:48 -- 11:06 AM @ C4.5
Stochastic Variance Reduction Methods for Policy Evaluation
Simon Du · Jianshu Chen · Lihong Li · Lin Xiao · Dengyong Zhou
Talk
Tue Aug 8th 10:48 -- 11:06 AM @ C4.9& C4.10
Exact Inference for Integer Latent-Variable Models
Kevin Winner · Debora Sujono · Daniel Sheldon
Talk
Tue Aug 8th 10:48 -- 11:06 AM @ C4.1
Bayesian inference on random simple graphs with power law degree distributions
Juho Lee · Creighton Heaukulani · Zoubin Ghahramani · Lancelot F. James · Seungjin Choi
Talk
Tue Aug 8th 10:48 -- 11:06 AM @ C4.4
Faster Principal Component Regression and Stable Matrix Chebyshev Approximation
Zeyuan Allen-Zhu · Yuanzhi Li
Talk
Tue Aug 8th 10:48 -- 11:06 AM @ C4.8
Estimating the unseen from multiple populations
Aditi Raghunathan · Greg Valiant · James Zou
Talk
Tue Aug 8th 10:48 -- 11:06 AM @ C4.6 & C4.7
Consistent k-Clustering
Silvio Lattanzi · Sergei Vassilvitskii
Talk
Tue Aug 8th 11:06 -- 11:24 AM @ Darling Harbour Theatre
Continual Learning Through Synaptic Intelligence
Friedemann Zenke · Ben Poole · Surya Ganguli
Talk
Tue Aug 8th 11:06 -- 11:24 AM @ Parkside 1
Tunable Efficient Unitary Neural Networks (EUNN) and their application to RNNs
Li Jing · Yichen Shen · Tena Dubcek · John E Peurifoy · Scott Skirlo · Yann LeCun · Max Tegmark · Marin Solja\v{c}i\'{c}
Talk
Tue Aug 8th 11:06 -- 11:24 AM @ Parkside 2
SARAH: A Novel Method for Machine Learning Problems Using Stochastic Recursive Gradient
Lam M Nguyen · Jie Liu · Katya Scheinberg · Martin Takac
Talk
Tue Aug 8th 11:06 -- 11:24 AM @ C4.5
Optimal and Adaptive Off-policy Evaluation in Contextual Bandits
Yu-Xiang Wang · Alekh Agarwal · Miroslav Dudik
Talk
Tue Aug 8th 11:06 -- 11:24 AM @ C4.9& C4.10
Improving Viterbi is Hard: Better Runtimes Imply Faster Clique Algorithms
Arturs Backurs · Christos Tzamos
Talk
Tue Aug 8th 11:06 -- 11:24 AM @ C4.1
Analogical Inference for Multi-relational Embeddings
Hanxiao Liu · Yuexin Wu · Yiming Yang
Talk
Tue Aug 8th 11:06 -- 11:24 AM @ C4.4
Spectral Learning from a Single Trajectory under Finite-State Policies
Borja de Balle Pigem · Odalric Maillard
Talk
Tue Aug 8th 11:06 -- 11:24 AM @ C4.8
Meritocratic Fairness for Cross-Population Selection
Michael Kearns · Aaron Roth · Steven Wu
Talk
Tue Aug 8th 11:06 -- 11:24 AM @ C4.6 & C4.7
Towards K-means-friendly Spaces: Simultaneous Deep Learning and Clustering
Bo Yang · Xiao Fu · Nicholas Sidiropoulos · Mingyi Hong
Talk
Tue Aug 8th 11:24 -- 11:42 AM @ Darling Harbour Theatre
Adaptive Neural Networks for Efficient Inference
Tolga Bolukbasi · Joseph Wang · Ofer Dekel · Venkatesh Saligrama
Talk
Tue Aug 8th 11:24 -- 11:42 AM @ Parkside 1
The Statistical Recurrent Unit
Junier Oliva · Barnabás Póczos · Jeff Schneider
Talk
Tue Aug 8th 11:24 -- 11:42 AM @ Parkside 2
Approximate Steepest Coordinate Descent
Sebastian Stich · Anant Raj · Martin Jaggi
Talk
Tue Aug 8th 11:24 -- 11:42 AM @ C4.5
Consistent On-Line Off-Policy Evaluation
Assaf Hallak · Shie Mannor
Talk
Tue Aug 8th 11:24 -- 11:42 AM @ C4.9& C4.10
Variational Inference for Sparse and Undirected Models
John Ingraham · Debora Marks
Talk
Tue Aug 8th 11:24 -- 11:42 AM @ C4.1
Know-Evolve: Deep Temporal Reasoning for Dynamic Knowledge Graphs
Rakshit Trivedi · Hajun Dai · Yichen Wang · Le Song
Talk
Tue Aug 8th 11:24 -- 11:42 AM @ C4.4
Capacity Releasing Diffusion for Speed and Locality.
Di Wang · Kimon Fountoulakis · Monika Henzinger · Michael Mahoney · Satish Rao
Talk
Tue Aug 8th 11:24 -- 11:42 AM @ C4.8
Neural networks and rational functions
Matus Telgarsky
Talk
Tue Aug 8th 11:24 -- 11:42 AM @ C4.6 & C4.7
Hyperplane Clustering Via Dual Principal Component Pursuit
Manolis Tsakiris · Rene Vidal
Talk
Tue Aug 8th 11:42 AM -- 12:00 PM @ Darling Harbour Theatre
Combined Group and Exclusive Sparsity for Deep Neural Networks
jaehong yoon · Sung Ju Hwang
Talk
Tue Aug 8th 11:42 AM -- 12:00 PM @ Parkside 1
Input Switched Affine Networks: An RNN Architecture Designed for Interpretability
Jakob Foerster · Justin Gilmer · Jan Chorowski · Jascha Sohl-Dickstein · David Sussillo
Talk
Tue Aug 8th 11:42 AM -- 12:00 PM @ Parkside 2
StingyCD: Safely Avoiding Wasteful Updates in Coordinate Descent
Tyler Johnson · Carlos Guestrin
Talk
Tue Aug 8th 11:42 AM -- 12:00 PM @ C4.5
Contextual Decision Processes with low Bellman rank are PAC-Learnable
Nan Jiang · Akshay Krishnamurthy · Alekh Agarwal · John Langford · Robert Schapire
Talk
Tue Aug 8th 11:42 AM -- 12:00 PM @ C4.9& C4.10
Tensor Belief Propagation
Andrew Wrigley · Wee Sun Lee · Nan Ye
Talk
Tue Aug 8th 11:42 AM -- 12:00 PM @ C4.1
Deep Generative Models for Relational Data with Side Information
Changwei Hu · Piyush Rai · Lawrence Carin
Talk
Tue Aug 8th 11:42 AM -- 12:00 PM @ C4.4
Doubly Accelerated Methods for Faster CCA and Generalized Eigendecomposition
Zeyuan Allen-Zhu · Yuanzhi Li
Talk
Tue Aug 8th 11:42 AM -- 12:00 PM @ C4.6 & C4.7
Multilevel Clustering via Wasserstein Means
Nhat Ho · Long Nguyen · Mikhail Yurochkin · Hung Bui · Viet Huynh · Dinh Phung
Break
Tue Aug 8th 12:00 -- 01:30 PM @
Lunch on your own
Talk
Tue Aug 8th 01:30 -- 01:48 PM @ Darling Harbour Theatre
Input Convex Neural Networks
Brandon Amos · Lei Xu · Zico Kolter
Talk
Tue Aug 8th 01:30 -- 01:48 PM @ Parkside 1
Online and Linear-Time Attention by Enforcing Monotonic Alignments
Colin Raffel · Thang Luong · Peter Liu · Ron Weiss · Douglas Eck
Talk
Tue Aug 8th 01:30 -- 01:48 PM @ Parkside 2
Stochastic modified equations and adaptive stochastic gradient algorithms
Qianxiao Li · Cheng Tai · Weinan E
Talk
Tue Aug 8th 01:30 -- 01:48 PM @ C4.5
A Simple Multi-Class Boosting Framework with Theoretical Guarantees and Empirical Proficiency
Ron Appel · Pietro Perona
Talk
Tue Aug 8th 01:30 -- 01:48 PM @ C4.9& C4.10
Faster Greedy MAP Inference for Determinantal Point Processes
Insu Han · Prabhanjan Kambadur · Kyoungsoo Park · Jinwoo Shin
Talk
Tue Aug 8th 01:30 -- 01:48 PM @ C4.1
ChoiceRank: Identifying Preferences from Node Traffic in Networks
Lucas Maystre · Matthias Grossglauser
Talk
Tue Aug 8th 01:30 -- 01:48 PM @ C4.4
On the Iteration Complexity of Support Recovery via Hard Thresholding Pursuit
Jie Shen · Ping Li
Talk
Tue Aug 8th 01:30 -- 01:48 PM @ C4.8
Uniform Deviation Bounds for k-Means Clustering
Olivier Bachem · Mario Lucic · Hamed Hassani · Andreas Krause
Talk
Tue Aug 8th 01:30 -- 01:48 PM @ C4.6 & C4.7
Co-clustering through Optimal Transport
Charlotte Laclau · Ievgen Redko · Basarab Matei · Younès Bennani · Vincent Brault
Talk
Tue Aug 8th 01:48 -- 02:06 PM @ Darling Harbour Theatre
OptNet: Differentiable Optimization as a Layer in Neural Networks
Brandon Amos · Zico Kolter
Talk
Tue Aug 8th 01:48 -- 02:06 PM @ Parkside 1
Sequence Tutor: Conservative fine-tuning of sequence generation models with KL-control
Natasha Jaques · Shixiang Gu · Dzmitry Bahdanau · Jose Hernandez-Lobato · Richard E Turner · Douglas Eck
Talk
Tue Aug 8th 01:48 -- 02:06 PM @ Parkside 2
Dissipativity Theory for Nesterov's Accelerated Method
Bin Hu · Laurent Lessard
Talk
Tue Aug 8th 01:48 -- 02:06 PM @ C4.5
Gradient Boosted Decision Trees for High Dimensional Sparse Output
Si Si · Huan Zhang · Sathiya Keerthi · Dhruv Mahajan · Inderjit Dhillon · Cho-Jui Hsieh
Talk
Tue Aug 8th 01:48 -- 02:06 PM @ C4.9& C4.10
Zonotope hit-and-run for efficient sampling from projection DPPs
Guillaume Gautier · Rémi Bardenet · Michal Valko
Talk
Tue Aug 8th 01:48 -- 02:06 PM @ C4.1
Statistical Inference for Incomplete Ranking Data: The Case of Rank-Dependent Coarsening
Mohsen Ahmadi Fahandar · Eyke Hüllermeier · Ines Couso
Talk
Tue Aug 8th 01:48 -- 02:06 PM @ C4.4
Dual Iterative Hard Thresholding: From Non-convex Sparse Minimization to Non-smooth Concave Maximization
Bo Liu · Xiaotong Yuan · Lezi Wang · Qingshan Liu · Dimitris Metaxas
Talk
Tue Aug 8th 01:48 -- 02:06 PM @ C4.8
Uniform Convergence Rates for Kernel Density Estimation
Heinrich Jiang
Talk
Tue Aug 8th 01:48 -- 02:06 PM @ C4.6 & C4.7
Multiple Clustering Views from Multiple Uncertain Experts
Yale Chang · Junxiang Chen · Michael Cho · Peter Castaldi · Edwin Silverman · Jennifer G Dy
Talk
Tue Aug 8th 02:06 -- 02:24 PM @ Darling Harbour Theatre
Parseval Networks: Improving Robustness to Adversarial Examples
Moustapha Cisse · Piotr Bojanowski · Edouard Grave · Yann Dauphin · Nicolas Usunier
Talk
Tue Aug 8th 02:06 -- 02:24 PM @ Parkside 1
Deep Voice: Real-time Neural Text-to-Speech
Andrew Gibiansky · Mike Chrzanowski · Mohammad Shoeybi · Shubho Sengupta · Gregory Diamos · Sercan Arik · Jonathan Raiman · John Miller · Xian Li · Yongguo Kang · Adam Coates · Andrew Ng
Talk
Tue Aug 8th 02:06 -- 02:24 PM @ Parkside 2
An Analytical Formula of Population Gradient for two-layered ReLU network and its Applications in Convergence and Critical Point Analysis
Yuandong Tian
Talk
Tue Aug 8th 02:06 -- 02:24 PM @ C4.5
Globally Induced Forest: A Prepruning Compression Scheme
Jean-Michel Begon · Arnaud Joly · Pierre Geurts
Talk
Tue Aug 8th 02:06 -- 02:24 PM @ C4.9& C4.10
A Divergence Bound for Hybrids of MCMC and Variational Inference and an Application to Langevin Dynamics and SGVI
Justin Domke
Talk
Tue Aug 8th 02:06 -- 02:24 PM @ C4.1
Just Sort It! A Simple and Effective Approach to Active Preference Learning
Lucas Maystre · Matthias Grossglauser
Talk
Tue Aug 8th 02:06 -- 02:24 PM @ C4.4
On The Projection Operator to A Three-view Cardinality Constrained Set
Haichuan Yang · Shupeng Gui · Chuyang Ke · Daniel Stefankovic · Ryohei Fujimaki · Ji Liu
Talk
Tue Aug 8th 02:06 -- 02:24 PM @ C4.8
Density Level Set Estimation on Manifolds with DBSCAN
Heinrich Jiang
Talk
Tue Aug 8th 02:06 -- 02:24 PM @ C4.6 & C4.7
Clustering by Sum of Norms: Stochastic Incremental Algorithm, Convergence and Cluster Recovery
Ashkan Panahi · Devdatt Dubhashi · Fredrik D Johansson · Chiranjib Bhattacharya
Talk
Tue Aug 8th 02:24 -- 02:42 PM @ Darling Harbour Theatre
Regularising Non-linear Models Using Feature Side-information
Amina Mollaysa · Pablo Strasser · Alexandros Kalousis
Talk
Tue Aug 8th 02:24 -- 02:42 PM @ Parkside 1
DeepBach: a Steerable Model for Bach Chorales Generation
Gaëtan HADJERES · François Pachet · Frank Nielsen
Talk
Tue Aug 8th 02:24 -- 02:42 PM @ Parkside 2
Forward and Reverse Gradient-Based Hyperparameter Optimization
Luca Franceschi · Michele Donini · Paolo Frasconi · Massimiliano Pontil
Talk
Tue Aug 8th 02:24 -- 02:42 PM @ C4.5
Forest-type Regression with General Losses and Robust Forest
Hanbo Li · Andrew Martin
Talk
Tue Aug 8th 02:24 -- 02:42 PM @ C4.9& C4.10
On the Sampling Problem for Kernel Quadrature
Francois-Xavier Briol · Chris J Oates · Jon Cockayne · Wilson Ye Chen · Mark Girolami
Talk
Tue Aug 8th 02:24 -- 02:42 PM @ C4.1
Maximum Selection and Ranking under Noisy Comparisons
Moein Falahatgar · Alon Orlitsky · Venkatadheeraj Pichapati · Ananda Suresh
Talk
Tue Aug 8th 02:24 -- 02:42 PM @ C4.4
Sparse + Group-Sparse Dirty Models: Statistical Guarantees without Unreasonable Conditions and a Case for Non-Convexity
Eunho Yang · Aurelie Lozano
Talk
Tue Aug 8th 02:24 -- 02:42 PM @ C4.8
Algorithmic Stability and Hypothesis Complexity
Tongliang Liu · Gábor Lugosi · Gergely Neu · Dacheng Tao
Talk
Tue Aug 8th 02:24 -- 02:42 PM @ C4.6 & C4.7
Clustering High Dimensional Dynamic Data Streams
Lin Yang · Harry Lang · Christian Sohler · Vladimir Braverman · Gereon Frahling
Talk
Tue Aug 8th 02:42 -- 03:00 PM @ Parkside 1
Neural Audio Synthesis of Musical Notes with WaveNet Autoencoders
Cinjon Resnick · Adam Roberts · Jesse Engel · Douglas Eck · Sander Dieleman · Karen Simonyan · Mohammad Norouzi
Talk
Tue Aug 8th 02:42 -- 03:00 PM @ Parkside 2
Adaptive Sampling Probabilities for Non-Smooth Optimization
Hongseok Namkoong · Aman Sinha · Steven Yadlowsky · John Duchi
Talk
Tue Aug 8th 02:42 -- 03:00 PM @ C4.5
Confident Multiple Choice Learning
Kimin Lee · Changho Hwang · KyoungSoo Park · Jinwoo Shin
Talk
Tue Aug 8th 02:42 -- 03:00 PM @ C4.9& C4.10
Measuring Sample Quality with Kernels
Jackson Gorham · Lester Mackey
Talk
Tue Aug 8th 02:42 -- 03:00 PM @ C4.1
Active Learning for Top-$K$ Rank Aggregation from Noisy Comparisons
Soheil Mohajer · Changho Suh · Adel Elmahdy
Talk
Tue Aug 8th 02:42 -- 03:00 PM @ C4.4
Compressed Sensing using Generative Models
Ashish Bora · Ajil Jalal · Eric Price · Alexandros Dimakis
Talk
Tue Aug 8th 02:42 -- 03:00 PM @ C4.8
Consistency Analysis for Binary Classification Revisited
Krzysztof Dembczynski · Wojciech Kotlowski · Oluwasanmi Koyejo · Nagarajan Natarajan
Break
Tue Aug 8th 03:00 -- 03:30 PM @ The Gallery
Coffee Break
Talk
Tue Aug 8th 03:30 -- 03:48 PM @ Darling Harbour Theatre
A Closer Look at Memorization in Deep Networks
David Krueger · Yoshua Bengio · Stanislaw Jastrzebsk · Maxinder S. Kanwal · Nicolas Ballas · Asja Fischer · Emmanuel Bengio · Devansh Arpit · Tegan Maharaj · Aaron Courville · Simon Lacoste-Julien
Talk
Tue Aug 8th 03:30 -- 03:48 PM @ Parkside 1
Learning to Generate Long-term Future via Hierarchical Prediction
Ruben Villegas · Jimei Yang · Yuliang Zou · Sungryull Sohn · Xunyu Lin · Honglak Lee
Talk
Tue Aug 8th 03:30 -- 03:48 PM @ Parkside 2
Sub-sampled Cubic Regularization for Non-convex Optimization
Jonas Kohler · Aurelien Lucchi
Talk
Tue Aug 8th 03:30 -- 03:48 PM @ C4.5
Regret Minimization in Behaviorally-Constrained Zero-Sum Games
Gabriele Farina · Christian Kroer · Tuomas Sandholm
Talk
Tue Aug 8th 03:30 -- 03:48 PM @ C4.9& C4.10
Variational Boosting: Iteratively Refining Posterior Approximations
Andrew Miller · Nicholas J Foti · Ryan Adams
Talk
Tue Aug 8th 03:30 -- 03:48 PM @ C4.1
Learning to Align the Source Code to the Compiled Object Code
Dor Levy · Lior Wolf
Talk
Tue Aug 8th 03:30 -- 03:48 PM @ C4.4
Scaling Up Sparse Support Vector Machines by Simultaneous Feature and Sample Reduction
Weizhong Zhang · Bin Hong · Wei Liu · Jieping Ye · Deng Cai · Xiaofei He · Jie Wang
Talk
Tue Aug 8th 03:30 -- 03:48 PM @ C4.8
Distributed Mean Estimation with Limited Communication
Ananda Suresh · Felix Yu · Sanjiv Kumar · H. Brendan McMahan
Talk
Tue Aug 8th 03:30 -- 03:48 PM @ C4.6 & C4.7
Fast k-Nearest Neighbour Search via Prioritized DCI
Ke Li · Jitendra Malik
Talk
Tue Aug 8th 03:48 -- 04:06 PM @ Darling Harbour Theatre
Cognitive Psychology for Deep Neural Networks: A Shape Bias Case Study
Samuel Ritter · David GT Barrett · Adam Santoro · Matthew Botvinick
Talk
Tue Aug 8th 03:48 -- 04:06 PM @ Parkside 1
Sequence to Better Sequence: Continuous Revision of Combinatorial Structures
Jonas Mueller · David Gifford · Tommi Jaakkola
Talk
Tue Aug 8th 03:48 -- 04:06 PM @ Parkside 2
Natasha: Faster Non-Convex Stochastic Optimization Via Strongly Non-Convex Parameter
Zeyuan Allen-Zhu
Talk
Tue Aug 8th 03:48 -- 04:06 PM @ C4.5
Reduced Space and Faster Convergence in Imperfect-Information Games via Pruning
Noam Brown · Tuomas Sandholm
Talk
Tue Aug 8th 03:48 -- 04:06 PM @ C4.9& C4.10
Lost Relatives of the Gumbel Trick
Matej Balog · Nilesh Tripuraneni · Zoubin Ghahramani · Adrian Weller
Talk
Tue Aug 8th 03:48 -- 04:06 PM @ C4.1
RobustFill: Neural Program Learning under Noisy I/O
Jacob Devlin · Jonathan Uesato · Surya Bhupatiraju · Rishabh Singh · Abdelrahman Mohammad · Pushmeet Kohli
Talk
Tue Aug 8th 03:48 -- 04:06 PM @ C4.4
Efficient Distributed Learning with Sparsity
Jialei Wang · Mladen Kolar · Nati Srebro · Tong Zhang
Talk
Tue Aug 8th 03:48 -- 04:06 PM @ C4.8
Nonparanormal Information Estimation
Shashank Singh · Barnabás Póczos
Talk
Tue Aug 8th 03:48 -- 04:06 PM @ C4.6 & C4.7
Deep Spectral Clustering Learning
Marc Law · Raquel Urtasun · Zemel Rich
Talk
Tue Aug 8th 04:06 -- 04:24 PM @ Darling Harbour Theatre
Visualizing and Understanding Multilayer Perceptron Models: A Case Study in Speech Processing
Tasha Nagamine · Nima Mesgarani
Talk
Tue Aug 8th 04:06 -- 04:24 PM @ Parkside 1
Tensor-Train Recurrent Neural Networks for Video Classification
Yinchong Yang · Denis Krompass · Volker Tresp
Talk
Tue Aug 8th 04:06 -- 04:24 PM @ Parkside 2
“Convex Until Proven Guilty”: Dimension-Free Acceleration of Gradient Descent on Non-Convex Functions
Yair Carmon · John Duchi · Oliver Hinder · Aaron Sidford
Talk
Tue Aug 8th 04:06 -- 04:24 PM @ C4.5
Strongly-Typed Agents are Guaranteed to Interact Safely
David Balduzzi
Talk
Tue Aug 8th 04:06 -- 04:24 PM @ C4.9& C4.10
Learning to Aggregate Ordinal Labels by Maximizing Separating Width
Guangyong Chen · Shengyu Zhang · Di Lin · Hui Huang · Pheng Ann Heng
Talk
Tue Aug 8th 04:06 -- 04:24 PM @ C4.1
Programming with a Differentiable Forth Interpreter
Matko Bošnjak · Tim Rocktäschel · Jason Naradowsky · Sebastian Riedel
Talk
Tue Aug 8th 04:06 -- 04:24 PM @ C4.4
Innovation Pursuit: A New Approach to the Subspace Clustering Problem
Mostafa Rahmani · George Atia
Talk
Tue Aug 8th 04:06 -- 04:24 PM @ C4.8
A Unified Maximum Likelihood Approach for Estimating Symmetric Properties of Discrete Distributions
Jayadev Acharya · Hirakendu Das · Alon Orlitsky · Ananda Suresh
Talk
Tue Aug 8th 04:06 -- 04:24 PM @ C4.6 & C4.7
Joint Dimensionality Reduction and Metric Learning: A Geometric Take
Mehrtash Harandi · Mathieu Salzmann · Richard I Hartley
Talk
Tue Aug 8th 04:24 -- 04:42 PM @ Darling Harbour Theatre
Axiomatic Attribution for Deep Networks
Mukund Sundararajan · Ankur Taly · Qiqi Yan
Talk
Tue Aug 8th 04:24 -- 04:42 PM @ Parkside 1
Sequence Modeling via Segmentations
Chong Wang · Yining Wang · Po-Sen Huang · Abdelrahman Mohammad · Dengyong Zhou · Li Deng
Talk
Tue Aug 8th 04:24 -- 04:42 PM @ Parkside 2
Convergence Analysis of Proximal Gradient with Momentum for Nonconvex Optimization
Qunwei Li · Yi Zhou · Yingbin Liang · Pramod K Varshney
Talk
Tue Aug 8th 04:24 -- 04:42 PM @ C4.5
Coordinated Multi-Agent Imitation Learning
Hoang Le · Yisong Yue · Peter Carr · Patrick Lucey
Talk
Tue Aug 8th 04:24 -- 04:42 PM @ C4.9& C4.10
Uncorrelation and Evenness: a New Diversity-Promoting Regularizer
Pengtao Xie · Aarti Singh · Eric Xing
Talk
Tue Aug 8th 04:24 -- 04:42 PM @ C4.1
Differentiable Programs with Neural Libraries
Alex Gaunt · Marc Brockschmidt · Nate Kushman · Daniel Tarlow
Talk
Tue Aug 8th 04:24 -- 04:42 PM @ C4.4
Selective Inference for Sparse High-Order Interaction Models
Shinya Suzumura · Kazuya Nakagawa · Yuta Umezu · Koji Tsuda · Ichiro Takeuchi
Talk
Tue Aug 8th 04:24 -- 04:42 PM @ C4.8
Gradient Coding: Avoiding Stragglers in Distributed Learning
Rashish Tandon · Qi Lei · Alexandros Dimakis · NIKOS KARAMPATZIAKIS
Talk
Tue Aug 8th 04:24 -- 04:42 PM @ C4.6 & C4.7
ProtoNN: Compressed and Accurate kNN for Resource-scarce Devices
Chirag Gupta · ARUN SUGGALA · Ankit Goyal · Saurabh Goyal · Ashish Kumar · Bhargavi Paranjape · Harsha Vardhan Simhadri · Raghavendra Udupa · Manik Varma · Prateek Jain
Talk
Tue Aug 8th 04:42 -- 05:00 PM @ Darling Harbour Theatre
On Calibration of Modern Neural Networks
Chuan Guo · Geoff Pleiss · Yu Sun · Kilian Weinberger
Talk
Tue Aug 8th 04:42 -- 05:00 PM @ Parkside 1
Latent LSTM Allocation: Joint clustering and non-linear dynamic modeling of sequence data
Manzil Zaheer · Amr Ahmed · Alex Smola
Talk
Tue Aug 8th 04:42 -- 05:00 PM @ Parkside 2
How to Escape Saddle Points Efficiently
Chi Jin · Rong Ge · Praneeth Netrapalli · Sham M. Kakade · Michael Jordan
Talk
Tue Aug 8th 04:42 -- 05:00 PM @ C4.5
Deep Decentralized Multi-task Multi-Agent Reinforcement Learning under Partial Observability
Shayegan Omidshafiei · Jason Pazis · Chris Amato · Jonathan How · John L Vian
Talk
Tue Aug 8th 04:42 -- 05:00 PM @ C4.9& C4.10
Learning Latent Space Models with Angular Constraints
Pengtao Xie · Yuntian Deng · Yi Zhou · Abhimanu Kumar · Yaoliang Yu · James Zou · Eric Xing
Talk
Tue Aug 8th 04:42 -- 05:00 PM @ C4.1
Developing Bug-Free Machine Learning Systems With Formal Mathematics
Daniel Selsam · Percy Liang · David L Dill
Talk
Tue Aug 8th 04:42 -- 05:00 PM @ C4.4
Dictionary Learning Based on Sparse Distribution Tomography
Pedram Pad · Farnood Salehi · Elisa Celis · Patrick Thiran · Michael Unser
Talk
Tue Aug 8th 04:42 -- 05:00 PM @ C4.8
Learning Discrete Representations via Information Maximizing Self-Augmented Training
Weihua Hu · Takeru Miyato · Seiya Tokui · Eiichi Matsumoto · Masashi Sugiyama
Invited Talk
Tue Aug 8th 05:15 -- 06:15 PM @ Darling Harbour Theatre
Genomics, Big Data, and Machine Learning: Understanding the Human Wiring Diagram and Driving the Healthcare Revolution
Peter Donnelly
Break
Tue Aug 8th 06:15 -- 07:00 PM @ Gallery
Light snack
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #1
The loss surface of deep and wide neural networks
Quynh Nguyen · Matthias Hein
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #2
Neural Taylor Approximations: Convergence and Exploration in Rectifier Networks
David Balduzzi · Brian McWilliams · Tony Butler-Yeoman
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #3
Sharp Minima Can Generalize For Deep Nets
Laurent Dinh · Razvan Pascanu · Samy Bengio · Yoshua Bengio
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #4
Geometry of Neural Network Loss Surfaces via Random Matrix Theory
Jeffrey Pennington · Yasaman Bahri
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #5
The Shattered Gradients Problem: If resnets are the answer, then what is the question?
David Balduzzi · Marcus Frean · Wan-Duo Ma · Brian McWilliams · Lennox Leary · John Lewis
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #6
Learning to Learn without Gradient Descent by Gradient Descent
Yutian Chen · Matthew Hoffman · Sergio Gómez Colmenarejo · Misha Denil · Timothy Lillicrap · Matthew Botvinick · Nando de Freitas
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #7
A Semismooth Newton Method for Fast, Generic Convex Programming
Alnur Ali · Eric Wong · Zico Kolter
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #8
Unifying task specification in reinforcement learning
Martha White
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #9
Efficient Online Bandit Multiclass Learning with O(sqrt{T}) Regret
Alina Beygelzimer · Francesco Orabona · Chicheng Zhang
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #10
Orthogonalized ALS: A Theoretically Principled Tensor Decomposition Algorithm for Practical Use
Vatsal Sharan · Gregory Valiant
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #11
Learned Optimizers that Scale and Generalize
Olga Wichrowska · Niru Maheswaranathan · Matthew Hoffman · Sergio Gómez Colmenarejo · Misha Denil · Nando de Freitas · Jascha Sohl-Dickstein
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #12
Approximate Newton Methods and Their Local Convergence
Haishan Ye · Luo Luo · Zhihua Zhang
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #13
A Distributional Perspective on Reinforcement Learning
Marc Bellemare · Will Dabney · Remi Munos
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #14
Active Learning for Accurate Estimation of Linear Models
Carlos Riquelme Ruiz · Mohammad Ghavamzadeh · Alessandro Lazaric
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #15
Tensor Decomposition via Simultaneous Power Iteration
Poan Wang · Chi-Jen Lu
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #16
Learning Gradient Descent: Better Generalization and Longer Horizons
Kaifeng Lv · Shunhua Jiang · Jian Li
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #17
Stochastic Adaptive Quasi-Newton Methods for Minimizing Expected Values
Chaoxu Zhou · Wenbo Gao · Donald Goldfarb
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #18
Hierarchy Through Composition with Multitask LMDPs
Andrew Saxe · Adam Earle · Benjamin Rosman
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #19
Adaptive Feature Selection: Computationally Efficient Online Sparse Linear Regression under RIP
Satyen Kale · Zohar Karnin · Tengyuan Liang · David Pal
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #20
A Unified Variance Reduction-Based Framework for Nonconvex Low-Rank Matrix Recovery
Lingxiao Wang · Xiao Zhang · Quanquan Gu
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #21
Learning Algorithms for Active Learning
Philip Bachman · Alessandro Sordoni · Adam Trischler
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #22
Practical Gauss-Newton Optimisation for Deep Learning
Aleksandar Botev · Julian Hippolyt Ritter · David Barber
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #23
A Laplacian Framework for Option Discovery in Reinforcement Learning
Marlos C. Machado · Marc Bellemare · Michael Bowling
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #24
Emulating the Expert: Inverse Optimization through Online Learning
Sebastian Pokutta · Andreas Bärmann · Oskar Schneider
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #25
An Efficient, Sparsity-Preserving, Online Algorithm for Low-Rank Approximation
David Anderson · Ming Gu
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #26
Tensor Balancing on Statistical Manifold
Mahito Sugiyama · Hiroyuki Nakahara · Koji Tsuda
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #27
Modular Multitask Reinforcement Learning with Policy Sketches
Jacob Andreas · Dan Klein · Sergey Levine
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #28
Variants of RMSProp and Adagrad with Logarithmic Regret Bounds
Mahesh Chandra Mukkamala · Matthias Hein
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #29
Algorithms for $\ell_p$ Low-Rank Approximation
Flavio Chierichetti · Sreenivas Gollapudi · Ravi Kumar · Silvio Lattanzi · Rina Panigrahy · David Woodruff
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #30
Relative Fisher Information and Natural Gradient for Learning Large Modular Models
Ke Sun · Frank Nielsen
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #31
Efficient Orthogonal Parametrisation of Recurrent Neural Networks Using Householder Reflections
zakaria mhammedi · Andrew Hellicar · James Bailey · Ashfaqur Rahman
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #32
Lazifying Conditional Gradient Algorithms
Gábor Braun · Sebastian Pokutta · Daniel Zink
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #33
Data-Efficient Policy Evaluation Through Behavior Policy Search
Josiah Hanna · Philip S. Thomas · Peter Stone · Scott Niekum
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #34
Exact MAP Inference by Avoiding Fractional Vertices
Erik Lindgren · Alexandros Dimakis · Adam Klivans
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #35
Leveraging Node Attributes for Incomplete Relational Data
He Zhao · Lan Du · Wray Buntine
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #36
How Close Are the Eigenvectors of the Sample and Actual Covariance Matrices?
Andreas Loukas
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #37
Distributed and Provably Good Seedings for k-Means in Constant Rounds
Olivier Bachem · Mario Lucic · Andreas Krause
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #38
Learning Deep Architectures via Generalized Whitened Neural Networks
Ping Luo
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #39
On orthogonality and learning RNNs with long term dependencies
Eugene Vorontsov · Chiheb Trabelsi · Christopher Pal · Samuel Kadoury
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #40
Conditional Accelerated Lazy Stochastic Gradient Descent
Guanghui · Sebastian Pokutta · Yi Zhou · Daniel Zink
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #41
Stochastic Variance Reduction Methods for Policy Evaluation
Simon Du · Jianshu Chen · Lihong Li · Lin Xiao · Dengyong Zhou
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #42
Exact Inference for Integer Latent-Variable Models
Kevin Winner · Debora Sujono · Daniel Sheldon
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #43
Bayesian inference on random simple graphs with power law degree distributions
Juho Lee · Creighton Heaukulani · Zoubin Ghahramani · Lancelot F. James · Seungjin Choi
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #44
Faster Principal Component Regression and Stable Matrix Chebyshev Approximation
Zeyuan Allen-Zhu · Yuanzhi Li
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #45
Consistent k-Clustering
Silvio Lattanzi · Sergei Vassilvitskii
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #46
Continual Learning Through Synaptic Intelligence
Friedemann Zenke · Ben Poole · Surya Ganguli
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #47
Tunable Efficient Unitary Neural Networks (EUNN) and their application to RNNs
Li Jing · Yichen Shen · Tena Dubcek · John E Peurifoy · Scott Skirlo · Yann LeCun · Max Tegmark · Marin Solja\v{c}i\'{c}
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #48
SARAH: A Novel Method for Machine Learning Problems Using Stochastic Recursive Gradient
Lam M Nguyen · Jie Liu · Katya Scheinberg · Martin Takac
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #49
Optimal and Adaptive Off-policy Evaluation in Contextual Bandits
Yu-Xiang Wang · Alekh Agarwal · Miroslav Dudik
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #50
Improving Viterbi is Hard: Better Runtimes Imply Faster Clique Algorithms
Arturs Backurs · Christos Tzamos
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #51
Analogical Inference for Multi-relational Embeddings
Hanxiao Liu · Yuexin Wu · Yiming Yang
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #52
Spectral Learning from a Single Trajectory under Finite-State Policies
Borja de Balle Pigem · Odalric Maillard
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #53
Towards K-means-friendly Spaces: Simultaneous Deep Learning and Clustering
Bo Yang · Xiao Fu · Nicholas Sidiropoulos · Mingyi Hong
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #54
Adaptive Neural Networks for Efficient Inference
Tolga Bolukbasi · Joseph Wang · Ofer Dekel · Venkatesh Saligrama
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #55
The Statistical Recurrent Unit
Junier Oliva · Barnabás Póczos · Jeff Schneider
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #56
Approximate Steepest Coordinate Descent
Sebastian Stich · Anant Raj · Martin Jaggi
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #57
Consistent On-Line Off-Policy Evaluation
Assaf Hallak · Shie Mannor
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #58
Variational Inference for Sparse and Undirected Models
John Ingraham · Debora Marks
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #59
Know-Evolve: Deep Temporal Reasoning for Dynamic Knowledge Graphs
Rakshit Trivedi · Hajun Dai · Yichen Wang · Le Song
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #60
Capacity Releasing Diffusion for Speed and Locality.
Di Wang · Kimon Fountoulakis · Monika Henzinger · Michael Mahoney · Satish Rao
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #61
Hyperplane Clustering Via Dual Principal Component Pursuit
Manolis Tsakiris · Rene Vidal
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #62
Combined Group and Exclusive Sparsity for Deep Neural Networks
jaehong yoon · Sung Ju Hwang
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #63
Input Switched Affine Networks: An RNN Architecture Designed for Interpretability
Jakob Foerster · Justin Gilmer · Jan Chorowski · Jascha Sohl-Dickstein · David Sussillo
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #64
StingyCD: Safely Avoiding Wasteful Updates in Coordinate Descent
Tyler Johnson · Carlos Guestrin
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #65
Contextual Decision Processes with low Bellman rank are PAC-Learnable
Nan Jiang · Akshay Krishnamurthy · Alekh Agarwal · John Langford · Robert Schapire
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #66
Tensor Belief Propagation
Andrew Wrigley · Wee Sun Lee · Nan Ye
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #67
Deep Generative Models for Relational Data with Side Information
Changwei Hu · Piyush Rai · Lawrence Carin
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #68
Doubly Accelerated Methods for Faster CCA and Generalized Eigendecomposition
Zeyuan Allen-Zhu · Yuanzhi Li
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #69
Multilevel Clustering via Wasserstein Means
Nhat Ho · Long Nguyen · Mikhail Yurochkin · Hung Bui · Viet Huynh · Dinh Phung
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #70
Online and Linear-Time Attention by Enforcing Monotonic Alignments
Colin Raffel · Thang Luong · Peter Liu · Ron Weiss · Douglas Eck
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #71
Stochastic modified equations and adaptive stochastic gradient algorithms
Qianxiao Li · Cheng Tai · Weinan E
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #72
A Simple Multi-Class Boosting Framework with Theoretical Guarantees and Empirical Proficiency
Ron Appel · Pietro Perona
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #73
Faster Greedy MAP Inference for Determinantal Point Processes
Insu Han · Prabhanjan Kambadur · Kyoungsoo Park · Jinwoo Shin
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #74
ChoiceRank: Identifying Preferences from Node Traffic in Networks
Lucas Maystre · Matthias Grossglauser
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #75
On the Iteration Complexity of Support Recovery via Hard Thresholding Pursuit
Jie Shen · Ping Li
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #76
Uniform Deviation Bounds for k-Means Clustering
Olivier Bachem · Mario Lucic · Hamed Hassani · Andreas Krause
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #77
Sequence Tutor: Conservative fine-tuning of sequence generation models with KL-control
Natasha Jaques · Shixiang Gu · Dzmitry Bahdanau · Jose Hernandez-Lobato · Richard E Turner · Douglas Eck
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #78
Dissipativity Theory for Nesterov's Accelerated Method
Bin Hu · Laurent Lessard
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #79
Gradient Boosted Decision Trees for High Dimensional Sparse Output
Si Si · Huan Zhang · Sathiya Keerthi · Dhruv Mahajan · Inderjit Dhillon · Cho-Jui Hsieh
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #80
Zonotope hit-and-run for efficient sampling from projection DPPs
Guillaume Gautier · Rémi Bardenet · Michal Valko
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #81
Statistical Inference for Incomplete Ranking Data: The Case of Rank-Dependent Coarsening
Mohsen Ahmadi Fahandar · Eyke Hüllermeier · Ines Couso
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #82
Dual Iterative Hard Thresholding: From Non-convex Sparse Minimization to Non-smooth Concave Maximization
Bo Liu · Xiaotong Yuan · Lezi Wang · Qingshan Liu · Dimitris Metaxas
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #83
Uniform Convergence Rates for Kernel Density Estimation
Heinrich Jiang
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #84
Deep Voice: Real-time Neural Text-to-Speech
Andrew Gibiansky · Mike Chrzanowski · Mohammad Shoeybi · Shubho Sengupta · Gregory Diamos · Sercan Arik · Jonathan Raiman · John Miller · Xian Li · Yongguo Kang · Adam Coates · Andrew Ng
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #85
An Analytical Formula of Population Gradient for two-layered ReLU network and its Applications in Convergence and Critical Point Analysis
Yuandong Tian
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #86
Globally Induced Forest: A Prepruning Compression Scheme
Jean-Michel Begon · Arnaud Joly · Pierre Geurts
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #87
A Divergence Bound for Hybrids of MCMC and Variational Inference and an Application to Langevin Dynamics and SGVI
Justin Domke
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #88
Just Sort It! A Simple and Effective Approach to Active Preference Learning
Lucas Maystre · Matthias Grossglauser
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #89
On The Projection Operator to A Three-view Cardinality Constrained Set
Haichuan Yang · Shupeng Gui · Chuyang Ke · Daniel Stefankovic · Ryohei Fujimaki · Ji Liu
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #90
Density Level Set Estimation on Manifolds with DBSCAN
Heinrich Jiang
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #91
DeepBach: a Steerable Model for Bach Chorales Generation
Gaëtan HADJERES · François Pachet · Frank Nielsen
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #92
Forward and Reverse Gradient-Based Hyperparameter Optimization
Luca Franceschi · Michele Donini · Paolo Frasconi · Massimiliano Pontil
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #93
Forest-type Regression with General Losses and Robust Forest
Hanbo Li · Andrew Martin
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #94
On the Sampling Problem for Kernel Quadrature
Francois-Xavier Briol · Chris J Oates · Jon Cockayne · Wilson Ye Chen · Mark Girolami
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #95
Maximum Selection and Ranking under Noisy Comparisons
Moein Falahatgar · Alon Orlitsky · Venkatadheeraj Pichapati · Ananda Suresh
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #96
Sparse + Group-Sparse Dirty Models: Statistical Guarantees without Unreasonable Conditions and a Case for Non-Convexity
Eunho Yang · Aurelie Lozano
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #97
Algorithmic Stability and Hypothesis Complexity
Tongliang Liu · Gábor Lugosi · Gergely Neu · Dacheng Tao
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #98
Neural Audio Synthesis of Musical Notes with WaveNet Autoencoders
Cinjon Resnick · Adam Roberts · Jesse Engel · Douglas Eck · Sander Dieleman · Karen Simonyan · Mohammad Norouzi
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #99
Adaptive Sampling Probabilities for Non-Smooth Optimization
Hongseok Namkoong · Aman Sinha · Steven Yadlowsky · John Duchi
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #100
Confident Multiple Choice Learning
Kimin Lee · Changho Hwang · KyoungSoo Park · Jinwoo Shin
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #101
Measuring Sample Quality with Kernels
Jackson Gorham · Lester Mackey
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #102
Active Learning for Top-$K$ Rank Aggregation from Noisy Comparisons
Soheil Mohajer · Changho Suh · Adel Elmahdy
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #103
Compressed Sensing using Generative Models
Ashish Bora · Ajil Jalal · Eric Price · Alexandros Dimakis
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #104
Consistency Analysis for Binary Classification Revisited
Krzysztof Dembczynski · Wojciech Kotlowski · Oluwasanmi Koyejo · Nagarajan Natarajan
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #105
A Closer Look at Memorization in Deep Networks
David Krueger · Yoshua Bengio · Stanislaw Jastrzebsk · Maxinder S. Kanwal · Nicolas Ballas · Asja Fischer · Emmanuel Bengio · Devansh Arpit · Tegan Maharaj · Aaron Courville · Simon Lacoste-Julien
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #106
Learning to Generate Long-term Future via Hierarchical Prediction
Ruben Villegas · Jimei Yang · Yuliang Zou · Sungryull Sohn · Xunyu Lin · Honglak Lee
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #107
Sub-sampled Cubic Regularization for Non-convex Optimization
Jonas Kohler · Aurelien Lucchi
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #108
Regret Minimization in Behaviorally-Constrained Zero-Sum Games
Gabriele Farina · Christian Kroer · Tuomas Sandholm
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #109
Variational Boosting: Iteratively Refining Posterior Approximations
Andrew Miller · Nicholas J Foti · Ryan Adams
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #110
Learning to Align the Source Code to the Compiled Object Code
Dor Levy · Lior Wolf
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #111
Scaling Up Sparse Support Vector Machines by Simultaneous Feature and Sample Reduction
Weizhong Zhang · Bin Hong · Wei Liu · Jieping Ye · Deng Cai · Xiaofei He · Jie Wang
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #112
Distributed Mean Estimation with Limited Communication
Ananda Suresh · Felix Yu · Sanjiv Kumar · H. Brendan McMahan
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #113
Cognitive Psychology for Deep Neural Networks: A Shape Bias Case Study
Samuel Ritter · David GT Barrett · Adam Santoro · Matthew Botvinick
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #114
Sequence to Better Sequence: Continuous Revision of Combinatorial Structures
Jonas Mueller · David Gifford · Tommi Jaakkola
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #115
Natasha: Faster Non-Convex Stochastic Optimization Via Strongly Non-Convex Parameter
Zeyuan Allen-Zhu
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #116
Reduced Space and Faster Convergence in Imperfect-Information Games via Pruning
Noam Brown · Tuomas Sandholm
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #117
Lost Relatives of the Gumbel Trick
Matej Balog · Nilesh Tripuraneni · Zoubin Ghahramani · Adrian Weller
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #118
RobustFill: Neural Program Learning under Noisy I/O
Jacob Devlin · Jonathan Uesato · Surya Bhupatiraju · Rishabh Singh · Abdelrahman Mohammad · Pushmeet Kohli
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #119
Efficient Distributed Learning with Sparsity
Jialei Wang · Mladen Kolar · Nati Srebro · Tong Zhang
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #120
Nonparanormal Information Estimation
Shashank Singh · Barnabás Póczos
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #121
Visualizing and Understanding Multilayer Perceptron Models: A Case Study in Speech Processing
Tasha Nagamine · Nima Mesgarani
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #122
Tensor-Train Recurrent Neural Networks for Video Classification
Yinchong Yang · Denis Krompass · Volker Tresp
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #123
“Convex Until Proven Guilty”: Dimension-Free Acceleration of Gradient Descent on Non-Convex Functions
Yair Carmon · John Duchi · Oliver Hinder · Aaron Sidford
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #124
Strongly-Typed Agents are Guaranteed to Interact Safely
David Balduzzi
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #125
Learning to Aggregate Ordinal Labels by Maximizing Separating Width
Guangyong Chen · Shengyu Zhang · Di Lin · Hui Huang · Pheng Ann Heng
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #126
Programming with a Differentiable Forth Interpreter
Matko Bošnjak · Tim Rocktäschel · Jason Naradowsky · Sebastian Riedel
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #127
Innovation Pursuit: A New Approach to the Subspace Clustering Problem
Mostafa Rahmani · George Atia
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #128
A Unified Maximum Likelihood Approach for Estimating Symmetric Properties of Discrete Distributions
Jayadev Acharya · Hirakendu Das · Alon Orlitsky · Ananda Suresh
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #129
Axiomatic Attribution for Deep Networks
Mukund Sundararajan · Ankur Taly · Qiqi Yan
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #130
Sequence Modeling via Segmentations
Chong Wang · Yining Wang · Po-Sen Huang · Abdelrahman Mohammad · Dengyong Zhou · Li Deng
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #131
Convergence Analysis of Proximal Gradient with Momentum for Nonconvex Optimization
Qunwei Li · Yi Zhou · Yingbin Liang · Pramod K Varshney
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #132
Coordinated Multi-Agent Imitation Learning
Hoang Le · Yisong Yue · Peter Carr · Patrick Lucey
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #133
Uncorrelation and Evenness: a New Diversity-Promoting Regularizer
Pengtao Xie · Aarti Singh · Eric Xing
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #134
Differentiable Programs with Neural Libraries
Alex Gaunt · Marc Brockschmidt · Nate Kushman · Daniel Tarlow
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #135
Selective Inference for Sparse High-Order Interaction Models
Shinya Suzumura · Kazuya Nakagawa · Yuta Umezu · Koji Tsuda · Ichiro Takeuchi
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #136
Gradient Coding: Avoiding Stragglers in Distributed Learning
Rashish Tandon · Qi Lei · Alexandros Dimakis · NIKOS KARAMPATZIAKIS
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #137
On Calibration of Modern Neural Networks
Chuan Guo · Geoff Pleiss · Yu Sun · Kilian Weinberger
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #138
Latent LSTM Allocation: Joint clustering and non-linear dynamic modeling of sequence data
Manzil Zaheer · Amr Ahmed · Alex Smola
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #139
How to Escape Saddle Points Efficiently
Chi Jin · Rong Ge · Praneeth Netrapalli · Sham M. Kakade · Michael Jordan
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #140
Deep Decentralized Multi-task Multi-Agent Reinforcement Learning under Partial Observability
Shayegan Omidshafiei · Jason Pazis · Chris Amato · Jonathan How · John L Vian
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #141
Learning Latent Space Models with Angular Constraints
Pengtao Xie · Yuntian Deng · Yi Zhou · Abhimanu Kumar · Yaoliang Yu · James Zou · Eric Xing
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #142
Developing Bug-Free Machine Learning Systems With Formal Mathematics
Daniel Selsam · Percy Liang · David L Dill
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #143
Dictionary Learning Based on Sparse Distribution Tomography
Pedram Pad · Farnood Salehi · Elisa Celis · Patrick Thiran · Michael Unser
Poster
Tue Aug 8th 06:30 -- 10:00 PM @ Gallery #144
Learning Discrete Representations via Information Maximizing Self-Augmented Training
Weihua Hu · Takeru Miyato · Seiya Tokui · Eiichi Matsumoto · Masashi Sugiyama
Break
Wed Aug 9th 07:00 AM -- 06:00 PM @ Ground Level
Registration Desk
Break
Wed Aug 9th 08:15 -- 09:00 AM @ Gallery
Coffee Break
Invited Talk
Wed Aug 9th 09:00 -- 10:45 AM @ Darling Harbour Theatre
Towards Reinforcement Learning in the Real World
Raia Hadsell
Break
Wed Aug 9th 10:00 -- 10:30 AM @ The Gallery
Coffee Break
Talk
Wed Aug 9th 10:30 -- 10:48 AM @ Darling Harbour Theatre
Device Placement Optimization with Reinforcement Learning
Azalia Mirhoseini · Hieu Pham · Quoc Le · benoit steiner · Mohammad Norouzi · Rasmus Larsen · Yuefeng Zhou · Naveen Kumar · Samy Bengio · Jeff Dean
Talk
Wed Aug 9th 10:30 -- 10:48 AM @ Parkside 1
Dynamic Word Embeddings
Robert Bamler · Stephan Mandt
Talk
Wed Aug 9th 10:30 -- 10:48 AM @ Parkside 2
Asynchronous Stochastic Gradient Descent with Delay Compensation
Shuxin Zheng · Qi Meng · Taifeng Wang · Wei Chen · Nenghai Yu · Zhiming Ma · Tie-Yan Liu
Talk
Wed Aug 9th 10:30 -- 10:48 AM @ C4.5
Improving Stochastic Policy Gradients in Continuous Control with Deep Reinforcement Learning using the Beta Distribution
Po-Wei Chou · Daniel Maturana · Sebastian Scherer
Talk
Wed Aug 9th 10:30 -- 10:48 AM @ C4.9& C4.10
Fractional Langevin Monte Carlo: Exploring Levy Driven Stochastic Differential Equations for MCMC
Umut Simsekli
Talk
Wed Aug 9th 10:30 -- 10:48 AM @ C4.1
Preferential Bayesian Optmization
Javier González · Zhenwen Dai · Andreas Damianou · Neil Lawrence
Talk
Wed Aug 9th 10:30 -- 10:48 AM @ C4.4
Being Robust (in High Dimensions) Can Be Practical
Ilias Diakonikolas · Gautam Kamath · Daniel Kane · Jerry Li · Ankur Moitra · Alistair Stewart
Talk
Wed Aug 9th 10:30 -- 10:48 AM @ C4.8
Differentially Private Ordinary Least Squares
Or Sheffet
Talk
Wed Aug 9th 10:30 -- 10:48 AM @ C4.6 & C4.7
When can Multi-Site Datasets be Pooled for Regression? Hypothesis Tests, $\ell_2$-consistency and Neuroscience Applications
Hao Zhou · Yilin Zhang · Vamsi Ithapu · Sterling Johnson · Grace Wahba · Vikas Singh
Talk
Wed Aug 9th 10:48 -- 11:06 AM @ Darling Harbour Theatre
Deep Tensor Convolution on Multicores
David Budden · Alexander Matveev · Shibani Santurkar · Shraman Ray Chaudhuri · Nir Shavit
Talk
Wed Aug 9th 10:48 -- 11:06 AM @ Parkside 1
Gram-CTC: Automatic Unit Selection and Target Decomposition for Sequence Labelling
Hairong Liu · Zhenyao Zhu · Xiangang Li · Sanjeev Satheesh
Talk
Wed Aug 9th 10:48 -- 11:06 AM @ Parkside 2
Adaptive Consensus ADMM for Distributed Optimization
Zheng Xu · Gavin Taylor · Hao Li · Mario Figueiredo · Xiaoming Yuan · Tom Goldstein
Talk
Wed Aug 9th 10:48 -- 11:06 AM @ C4.5
Combining Model-Based and Model-Free Updates for Trajectory-Centric Reinforcement Learning
Yevgen Chebotar · Karol Hausman · Marvin Zhang · Gaurav Sukhatme · Stefan Schaal · Sergey Levine
Talk
Wed Aug 9th 10:48 -- 11:06 AM @ C4.9& C4.10
Stochastic Bouncy Particle Sampler
Ari Pakman · Dar Gilboa · David Carlson · Liam Paninski
Talk
Wed Aug 9th 10:48 -- 11:06 AM @ C4.1
Max-value Entropy Search for Efficient Bayesian Optimization
Zi Wang · Stefanie Jegelka
Talk
Wed Aug 9th 10:48 -- 11:06 AM @ C4.4
Multilabel Classification with Group Testing and Codes
Shashanka Ubaru · Arya Mazumdar
Talk
Wed Aug 9th 10:48 -- 11:06 AM @ C4.8
Priv’IT: Private and Sample Efficient Identity Testing
Bryan Cai · Constantinos Daskalakis · Gautam Kamath
Talk
Wed Aug 9th 10:48 -- 11:06 AM @ C4.6 & C4.7
Learning from Clinical Judgments: Semi-Markov-Modulated Marked Hawkes Processes for Risk Prognosis
Ahmed M. Alaa Ibrahim · Scott B Hu · Mihaela van der Schaar
Talk
Wed Aug 9th 11:06 -- 11:24 AM @ Darling Harbour Theatre
MEC: Memory-efficient Convolution for Deep Neural Network
Minsik Cho · Daniel Brand
Talk
Wed Aug 9th 11:06 -- 11:24 AM @ Parkside 1
Coupling Distributed and Symbolic Execution for Natural Language Queries
Lili Mou · Zhengdong Lu · Hang Li · Zhi Jin
Talk
Wed Aug 9th 11:06 -- 11:24 AM @ Parkside 2
Optimal Algorithms for Smooth and Strongly Convex Distributed Optimization in Networks
Kevin Scaman · Francis Bach · Sebastien Bubeck · Yin Tat Lee · Laurent Massoulié
Talk
Wed Aug 9th 11:06 -- 11:24 AM @ C4.5
Prediction under Uncertainty in Sparse Spectrum Gaussian Processes with Applications to Filtering and Control
Yunpeng Pan · Xinyan Yan · Evangelos Theodorou · Byron Boots
Talk
Wed Aug 9th 11:06 -- 11:24 AM @ C4.9& C4.10
Canopy --- Fast Sampling with Cover Trees
Manzil Zaheer · Satwik Kottur · Amr Ahmed · Jose Moura · Alex Smola
Talk
Wed Aug 9th 11:06 -- 11:24 AM @ C4.1
Bayesian Optimization with Tree-structured Dependencies
Rodolphe Jenatton · Cedric Archambeau · Javier González · Matthias Seeger
Talk
Wed Aug 9th 11:06 -- 11:24 AM @ C4.4
High-Dimensional Structured Quantile Regression
Vidyashankar Sivakumar · Arindam Banerjee
Talk
Wed Aug 9th 11:06 -- 11:24 AM @ C4.8
Differentially Private Submodular Maximization: Data Summarization in Disguise
Marko Mitrovic · Mark Bun · Andreas Krause · Amin Karbasi
Talk
Wed Aug 9th 11:06 -- 11:24 AM @ C4.6 & C4.7
Learning to Detect Sepsis with a Multitask Gaussian Process RNN Classifier
Joseph Futoma · Sanjay Hariharan · Katherine Heller
Talk
Wed Aug 9th 11:24 -- 11:42 AM @ Darling Harbour Theatre
Beyond Filters: Compact Feature Map for Portable Deep Model
Yunhe Wang · Chang Xu · Chao Xu · Dacheng Tao
Talk
Wed Aug 9th 11:24 -- 11:42 AM @ Parkside 1
Image-to-Markup Generation with Coarse-to-Fine Attention
Yuntian Deng · Anssi Kanervisto · Jeffrey Ling · Alexander Rush
Talk
Wed Aug 9th 11:24 -- 11:42 AM @ Parkside 2
Projection-free Distributed Online Learning in Networks
Wenpeng Zhang · Peilin Zhao · wenwu zhu · Steven Hoi · Tong Zhang
Talk
Wed Aug 9th 11:24 -- 11:42 AM @ C4.5
Learning Stable Stochastic Nonlinear Dynamical Systems
Jonas Umlauft · Sandra Hirche
Talk
Wed Aug 9th 11:24 -- 11:42 AM @ C4.9& C4.10
A Simulated Annealing Based Inexact Oracle for Wasserstein Loss Minimization
Jianbo Ye · James Wang · Jia Li
Talk
Wed Aug 9th 11:24 -- 11:42 AM @ C4.1
Multi-fidelity Bayesian Optimisation with Continuous Approximations
kirthevasan kandasamy · Gautam Dasarathy · Barnabás Póczos · Jeff Schneider
Talk
Wed Aug 9th 11:24 -- 11:42 AM @ C4.4
High-dimensional Non-Gaussian Single Index Models via Thresholded Score Function Estimation
Zhuoran Yang · Krishnakumar Balasubramanian · Han Liu
Talk
Wed Aug 9th 11:24 -- 11:42 AM @ C4.8
Differentially Private Learning of Graphical Models using CGMs
Garrett Bernstein · Ryan McKenna · Tao Sun · Daniel Sheldon · Michael Hay · Gerome Miklau
Talk
Wed Aug 9th 11:24 -- 11:42 AM @ C4.6 & C4.7
iSurvive: An Interpretable, Event-time Prediction Model for mHealth
Walter Dempsey · Alexander Moreno · Jim Rehg · Susan Murphy · Chris Scott · Michael Dennis · David Gustafson
Talk
Wed Aug 9th 11:42 AM -- 12:00 PM @ Darling Harbour Theatre
Efficient softmax approximation for GPUs
Edouard Grave · Armand Joulin · Moustapha Cisse · David Grangier · Herve Jegou
Talk
Wed Aug 9th 11:42 AM -- 12:00 PM @ Parkside 1
Multichannel End-to-end Speech Recognition
Tsubasa Ochiai · Shinji Watanabe · Takaaki Hori · John Hershey
Talk
Wed Aug 9th 11:42 AM -- 12:00 PM @ C4.5
Local Bayesian Optimization of Motor Skills
Riadh Akrour · Dmitry Sorokin · Jan Peters · Gerhard Neumann
Talk
Wed Aug 9th 11:42 AM -- 12:00 PM @ C4.9& C4.10
Improving Gibbs Sampler Scan Quality with DoGS
Ioannis Mitliagkas · Lester Mackey
Talk
Wed Aug 9th 11:42 AM -- 12:00 PM @ C4.1
Parallel and Distributed Thompson Sampling for Large-scale Accelerated Exploration of Chemical Space
Jose Hernandez-Lobato · James Requeima · Edward Pyzer-Knapp · alan Aspuru-Guzik
Talk
Wed Aug 9th 11:42 AM -- 12:00 PM @ C4.4
Robust Structured Estimation with Single-Index Models
Sheng Chen · Arindam Banerjee
Talk
Wed Aug 9th 11:42 AM -- 12:00 PM @ C4.8
Minimizing Trust Leaks for Robust Sybil Detection
János Höner · Shinichi Nakajima · Alexander Bauer · Klaus-robert Mueller · Nico Görnitz
Talk
Wed Aug 9th 11:42 AM -- 12:00 PM @ C4.6 & C4.7
Learning Sleep Stages from Radio Signals: A Conditional Adversarial Architecture
Mingmin Zhao · Shichao Yue · Dina Katabi · Tommi Jaakkola · Matt Bianchi
Break
Wed Aug 9th 12:00 -- 01:30 PM @
Lunch on your own
Break
Wed Aug 9th 12:00 -- 01:30 PM @ Parkside 1
Open Business Meeting
Talk
Wed Aug 9th 01:30 -- 01:48 PM @ Darling Harbour Theatre
Dropout Inference in Bayesian Neural Networks with Alpha-divergences
Yingzhen Li · Yarin Gal
Talk
Wed Aug 9th 01:30 -- 01:48 PM @ Parkside 1
Latent Intention Dialogue Models
Tsung-Hsien Wen · Yishu Miao · Phil Blunsom · Stephen J Young
Talk
Wed Aug 9th 01:30 -- 01:48 PM @ Parkside 2
Robust Guarantees of Stochastic Greedy Algorithms
Yaron Singer · Avinatan Hassidim
Talk
Wed Aug 9th 01:30 -- 01:48 PM @ C4.5
Count-Based Exploration with Neural Density Models
Georg Ostrovski · Marc Bellemare · Aäron van den Oord · Remi Munos
Talk
Wed Aug 9th 01:30 -- 01:48 PM @ C4.9& C4.10
Magnetic Hamiltonian Monte Carlo
Nilesh Tripuraneni · Mark Rowland · Zoubin Ghahramani · Richard E Turner
Talk
Wed Aug 9th 01:30 -- 01:48 PM @ C4.1
Uncertainty Assessment and False Discovery Rate Control in High-Dimensional Granger Causal Inference
Aditya Chaudhry · Pan Xu · Quanquan Gu
Talk
Wed Aug 9th 01:30 -- 01:48 PM @ C4.4
Toward Efficient and Accurate Covariance Matrix Estimation on Compressed Data
Xixian Chen · Michael Lyu · Irwin King
Talk
Wed Aug 9th 01:30 -- 01:48 PM @ C4.8
The Price of Differential Privacy For Online Learning
Naman Agarwal · Karan Singh
Talk
Wed Aug 9th 01:30 -- 01:48 PM @ C4.6 & C4.7
Bidirectional learning for time-series models with hidden units
Takayuki Osogami · Hiroshi Kajino · Taro Sekiyama
Talk
Wed Aug 9th 01:48 -- 02:06 PM @ Darling Harbour Theatre
Multiplicative Normalizing Flows for Variational Bayesian Neural Networks
Christos Louizos · Max Welling
Talk
Wed Aug 9th 01:48 -- 02:06 PM @ Parkside 1
Discovering Discrete Latent Topics with Neural Variational Inference
Yishu Miao · Edward Grefenstette · Phil Blunsom
Talk
Wed Aug 9th 01:48 -- 02:06 PM @ Parkside 2
Guarantees for Greedy Maximization of Non-submodular Functions with Applications
Andrew An Bian · Joachim Buhmann · Andreas Krause · Sebastian Tschiatschek
Talk
Wed Aug 9th 01:48 -- 02:06 PM @ C4.5
Zero-Shot Task Generalization with Multi-Task Deep Reinforcement Learning
Junhyuk Oh · Satinder Singh · Honglak Lee · Pushmeet Kohli
Talk
Wed Aug 9th 01:48 -- 02:06 PM @ C4.9& C4.10
Probabilistic Path Hamiltonian Monte Carlo
Vu Dinh · Arman Bilge · Cheng Zhang · Frederick Matsen
Talk
Wed Aug 9th 01:48 -- 02:06 PM @ C4.1
Uncovering Causality from Multivariate Hawkes Integrated Cumulants
Massil Achab · Emmanuel Bacry · Stéphane Gaïffas · Iacopo Mastromatteo · Jean-François Muzy
Talk
Wed Aug 9th 01:48 -- 02:06 PM @ C4.4
Robust Gaussian Graphical Model Estimation with Arbitrary Corruption
Lingxiao Wang · Quanquan Gu
Talk
Wed Aug 9th 01:48 -- 02:06 PM @ C4.8
Pain-Free Random Differential Privacy with Sensitivity Sampling
Benjamin Rubinstein · Francesco Aldà
Talk
Wed Aug 9th 01:48 -- 02:06 PM @ C4.6 & C4.7
Learning Hawkes Processes from Short Doubly-Censored Event Sequences
Hongteng Xu · Dixin Luo · Hongyuan Zha
Talk
Wed Aug 9th 02:06 -- 02:24 PM @ Darling Harbour Theatre
Variational Dropout Sparsifies Deep Neural Networks
Dmitry Molchanov · Arsenii Ashukha · Dmitry Vetrov
Talk
Wed Aug 9th 02:06 -- 02:24 PM @ Parkside 1
Toward Controlled Generation of Text
Zhiting Hu · Zichao Yang · Xiaodan Liang · Ruslan Salakhutdinov · Eric Xing
Talk
Wed Aug 9th 02:06 -- 02:24 PM @ Parkside 2
Robust Submodular Maximization: A Non-Uniform Partitioning Approach
Ilija Bogunovic · Slobodan Mitrovic · Jonathan Scarlett · Volkan Cevher
Talk
Wed Aug 9th 02:06 -- 02:24 PM @ C4.5
Stabilising Experience Replay for Deep Multi-Agent Reinforcement Learning
Jakob Foerster · Nantas Nardelli · Gregory Farquhar · Triantafyllos Afouras · Phil Torr · Pushmeet Kohli · Shimon Whiteson
Talk
Wed Aug 9th 02:06 -- 02:24 PM @ C4.9& C4.10
Stochastic Gradient Monomial Gamma Sampler
Yizhe Zhang · Changyou Chen · Zhe Gan · Ricardo Henao · Lawrence Carin
Talk
Wed Aug 9th 02:06 -- 02:24 PM @ C4.1
Cost-Optimal Learning of Causal Graphs
Murat Kocaoglu · Alexandros Dimakis · Sriram Vishwanath
Talk
Wed Aug 9th 02:06 -- 02:24 PM @ C4.4
Algebraic Variety Models for High-Rank Matrix Completion
Greg Ongie · Laura Balzano · Rebecca Willett · Robert Nowak
Talk
Wed Aug 9th 02:06 -- 02:24 PM @ C4.8
Differentially Private Clustering in High-Dimensional Euclidean Spaces
Nina Balcan · Travis Dick · Yingyu Liang · Wenlong Mou · Hongyang Zhang
Talk
Wed Aug 9th 02:06 -- 02:24 PM @ C4.6 & C4.7
Coherent probabilistic forecasts for hierarchical time series
Souhaib Ben Taieb · James Taylor · Rob Hyndman
Talk
Wed Aug 9th 02:24 -- 02:42 PM @ Darling Harbour Theatre
Unimodal Probability Distributions for Deep Ordinal Classification
Christopher Beckham · Christopher Pal
Talk
Wed Aug 9th 02:24 -- 02:42 PM @ Parkside 2
Probabilistic Submodular Maximization in Sub-Linear Time
Serban A Stan · Morteza Zadimoghaddam · Andreas Krause · Amin Karbasi
Talk
Wed Aug 9th 02:24 -- 02:42 PM @ C4.5
The Predictron: End-To-End Learning and Planning
David Silver · Hado van Hasselt · Matteo Hessel · Tom Schaul · Arthur Guez · Tim Harley · Gabriel Dulac-Arnold · David Reichert · Neil Rabinowitz · Andre Barreto · Thomas Degris
Talk
Wed Aug 9th 02:24 -- 02:42 PM @ C4.9& C4.10
Stochastic Gradient MCMC Methods for Hidden Markov Models
Yi-An Ma · Nicholas J Foti · Emily Fox
Talk
Wed Aug 9th 02:24 -- 02:42 PM @ C4.1
Identification and Model Testing in Linear Structural Equation Models using Auxiliary Variables
Bryant Chen · Daniel Kumor · Elias Bareinboim
Talk
Wed Aug 9th 02:24 -- 02:42 PM @ C4.4
High-Dimensional Variance-Reduced Stochastic Gradient Expectation-Maximization Algorithm
Rongda Zhu · Lingxiao Wang · Chengxiang Zhai · Quanquan Gu
Talk
Wed Aug 9th 02:24 -- 02:42 PM @ C4.8
Differentially Private Chi-squared Test by Unit Circle Mechanism
Kazuya Kakizaki · Kazuto Fukuchi · Jun Sakuma
Talk
Wed Aug 9th 02:24 -- 02:42 PM @ C4.6 & C4.7
Soft-DTW: a Differentiable Loss Function for Time-Series
Marco Cuturi · Mathieu Blondel
Talk
Wed Aug 9th 02:24 -- 02:42 PM @ Parkside 1
Learning Continuous Semantic Representations of Symbolic Expressions
Miltiadis Allamanis · pankajan Chanthirasegaran · Pushmeet Kohli · Charles Sutton
Talk
Wed Aug 9th 02:42 -- 03:00 PM @ Parkside 1
Adversarial Feature Matching for Text Generation
Yizhe Zhang · Zhe Gan · Kai Fan · Zhi Chen · Ricardo Henao · Dinghan Shen · Lawrence Carin
Talk
Wed Aug 9th 02:42 -- 03:00 PM @ Parkside 2
On Approximation Guarantees for Greedy Low Rank Optimization
RAJIV KHANNA · Ethan Elenberg · Alexandros Dimakis · Joydeep Ghosh · Sahand Negahban
Talk
Wed Aug 9th 02:42 -- 03:00 PM @ C4.5
Averaged-DQN: Variance Reduction and Stabilization for Deep Reinforcement Learning
Oron Anschel · Nir Baram · Nahum Shimkin
Talk
Wed Aug 9th 02:42 -- 03:00 PM @ C4.9& C4.10
Deep Latent Dirichlet Allocation with Topic-Layer-Adaptive Stochastic Gradient Riemannian MCMC
Yulai Cong · Bo Chen · Hongwei Liu · Mingyuan Zhou
Talk
Wed Aug 9th 02:42 -- 03:00 PM @ C4.1
Estimating individual treatment effect: generalization bounds and algorithms
Uri Shalit · Fredrik D Johansson · David Sontag
Talk
Wed Aug 9th 02:42 -- 03:00 PM @ C4.8
Collect at Once, Use Effectively: Making Non-interactive Locally Private Learning Possible
Kai Zheng · Wenlong Mou · Liwei Wang
Talk
Wed Aug 9th 02:42 -- 03:00 PM @ C4.6 & C4.7
Variational Policy for Guiding Point Processes
Yichen Wang · Grady Williams · Evangelos Theodorou · Le Song
Break
Wed Aug 9th 03:00 -- 03:30 PM @ The Gallery
Coffee Break
Talk
Wed Aug 9th 03:30 -- 03:48 PM @ Darling Harbour Theatre
Dance Dance Convolution
Christopher Donahue · Zachary Lipton · Julian McAuley
Talk
Wed Aug 9th 03:30 -- 03:48 PM @ Parkside 1
Language Modeling with Gated Convolutional Networks
Yann Dauphin · Angela Fan · Michael Auli · David Grangier
Talk
Wed Aug 9th 03:30 -- 03:48 PM @ Parkside 2
Deletion-Robust Submodular Maximization: Data Summarization with "the Right to be Forgotten"
Baharan Mirzasoleiman · Amin Karbasi · Andreas Krause
Talk
Wed Aug 9th 03:30 -- 03:48 PM @ C4.5
FeUdal Networks for Hierarchical Reinforcement Learning
Alexander Vezhnevets · Simon Osindero · Tom Schaul · Nicolas Heess · Max Jaderberg · David Silver · Koray Kavukcuoglu
Talk
Wed Aug 9th 03:30 -- 03:48 PM @ C4.9& C4.10
Distributed Batch Gaussian Process Optimization
Erik Daxberger · Bryan Kian Hsiang Low
Talk
Wed Aug 9th 03:30 -- 03:48 PM @ C4.1
Recursive Partitioning for Personalization using Observational Data
Nathan Kallus
Talk
Wed Aug 9th 03:30 -- 03:48 PM @ C4.4
Optimal Densification for Fast and Accurate Minwise Hashing
Anshumali Shrivastava
Talk
Wed Aug 9th 03:30 -- 03:48 PM @ C4.8
An Adaptive Test of Independence with Analytic Kernel Embeddings
Wittawat Jitkrittum · Zoltan Szabo · Arthur Gretton
Talk
Wed Aug 9th 03:30 -- 03:48 PM @ C4.6 & C4.7
Deep Value Networks Learn to Evaluate and Iteratively Refine Structured Outputs
Michael Gygli · Mohammad Norouzi · Anelia Angelova
Talk
Wed Aug 9th 03:48 -- 04:06 PM @ Darling Harbour Theatre
World of Bits: An Open-Domain Platform for Web-Based Agents
Tim Shi · Andrej Karpathy · Linxi Fan · Jonathan Hernandez · Percy Liang
Talk
Wed Aug 9th 03:48 -- 04:06 PM @ Parkside 1
Convolutional Sequence to Sequence Learning
Jonas Gehring · Michael Auli · David Grangier · Denis Yarats · Yann Dauphin
Talk
Wed Aug 9th 03:48 -- 04:06 PM @ Parkside 2
Analysis and Optimization of Graph Decompositions by Lifted Multicuts
Andrea Hornakova · Jan-Hendrik Lange · Bjoern Andres
Talk
Wed Aug 9th 03:48 -- 04:06 PM @ C4.5
Deciding How to Decide: Dynamic Routing in Artificial Neural Networks
Mason McGill · Pietro Perona
Talk
Wed Aug 9th 03:48 -- 04:06 PM @ C4.9& C4.10
Scalable Multi-Class Gaussian Process Classification using Expectation Propagation
Carlos Villacampa-Calvo · Daniel Hernandez-Lobato
Talk
Wed Aug 9th 03:48 -- 04:06 PM @ C4.1
Identifying Best Interventions through Online Importance Sampling
Rajat Sen · Karthikeyan Shanmugam · Alexandros Dimakis · Sanjay Shakkottai
Talk
Wed Aug 9th 03:48 -- 04:06 PM @ C4.4
Stochastic Generative Hashing
Bo Dai · Ruiqi Guo · Sanjiv Kumar · Niao He · Le Song
Talk
Wed Aug 9th 03:48 -- 04:06 PM @ C4.8
Sliced Wasserstein Kernel for Persistence Diagrams
Mathieu Carrière · Marco Cuturi · Steve Oudot
Talk
Wed Aug 9th 03:48 -- 04:06 PM @ C4.6 & C4.7
Deeply AggreVaTeD: Differentiable Imitation Learning for Sequential Prediction
Wen Sun · Arun Venkatraman · Geoff Gordon · Byron Boots · Drew Bagnell
Talk
Wed Aug 9th 04:06 -- 04:24 PM @ Darling Harbour Theatre
Real-Time Adaptive Image Compression
Oren Rippel · Lubomir Bourdev
Talk
Wed Aug 9th 04:06 -- 04:24 PM @ Parkside 1
Improved Variational Autoencoders for Text Modeling using Dilated Convolutions
Zichao Yang · Zhiting Hu · Ruslan Salakhutdinov · Taylor Berg-Kirkpatrick
Talk
Wed Aug 9th 04:06 -- 04:24 PM @ Parkside 2
Near-Optimal Design of Experiments via Regret Minimization
Zeyuan Allen-Zhu · Yuanzhi Li · Aarti Singh · Yining Wang
Talk
Wed Aug 9th 04:06 -- 04:24 PM @ C4.5
Neural Episodic Control
Alexander Pritzel · Benigno Uria · Srinivasan Sriram · Adrià Puigdomenech Badia · Oriol Vinyals · Demis Hassabis · Daan Wierstra · Charles Blundell
Talk
Wed Aug 9th 04:06 -- 04:24 PM @ C4.9& C4.10
Random Feature Expansions for Deep Gaussian Processes
Kurt Cutajar · Edwin Bonilla · Pietro Michiardi · Maurizio Filippone
Talk
Wed Aug 9th 04:06 -- 04:24 PM @ C4.1
Deep IV: A Flexible Approach for Counterfactual Prediction
Jason Hartford · Greg Lewis · Kevin Leyton-Brown · Matt Taddy
Talk
Wed Aug 9th 04:06 -- 04:24 PM @ C4.4
ZipML: Training Linear Models with End-to-End Low Precision, and a Little Bit of Deep Learning
Hantian Zhang · Jerry Li · Kaan Kara · Dan Alistarh · Ji Liu · Ce Zhang
Talk
Wed Aug 9th 04:06 -- 04:24 PM @ C4.8
Adapting Kernel Representations Online Using Submodular Maximization
Matthew Schlegel · Yangchen Pan · Jiecao Chen · Martha White
Talk
Wed Aug 9th 04:06 -- 04:24 PM @ C4.6 & C4.7
End-to-End Learning for Structured Prediction Energy Networks
David Belanger · Bishan Yang · Andrew McCallum
Talk
Wed Aug 9th 04:24 -- 04:42 PM @ Darling Harbour Theatre
Neural Message Passing for Quantum Chemistry
Justin Gilmer · Samuel Schoenholz · Patrick F Riley · Oriol Vinyals · George Dahl
Talk
Wed Aug 9th 04:24 -- 04:42 PM @ Parkside 1
Grammar Variational Autoencoder
Matt J. Kusner · Brooks Paige · Jose Hernandez-Lobato
Talk
Wed Aug 9th 04:24 -- 04:42 PM @ Parkside 2
Robust Budget Allocation via Continuous Submodular Functions
Matthew J Staib · Stefanie Jegelka
Talk
Wed Aug 9th 04:24 -- 04:42 PM @ C4.5
Neural Optimizer Search using Reinforcement Learning
Irwan Bello · Barret Zoph · Vijay Vasudevan · Quoc Le
Talk
Wed Aug 9th 04:24 -- 04:42 PM @ C4.9& C4.10
Asynchronous Distributed Variational Gaussian Processes for Regression
Hao Peng · Shandian Zhe · Xiao Zhang · Yuan Qi
Talk
Wed Aug 9th 04:24 -- 04:42 PM @ C4.1
Counterfactual Data-Fusion for Online Reinforcement Learners
Andrew Forney · Judea Pearl · Elias Bareinboim
Talk
Wed Aug 9th 04:24 -- 04:42 PM @ C4.4
Large-Scale Evolution of Image Classifiers
Esteban Real · Sherry Moore · Andrew Selle · Saurabh Saxena · Yutaka Leon Suematsu · Jie Tan · Quoc Le · Alexey Kurakin
Talk
Wed Aug 9th 04:24 -- 04:42 PM @ C4.8
Spherical Structured Feature Maps for Kernel Approximation
Yueming LYU
Talk
Wed Aug 9th 04:24 -- 04:42 PM @ C4.6 & C4.7
A Unified View of Multi-Label Performance Measures
Xi-Zhu Wu · Zhi-Hua Zhou
Talk
Wed Aug 9th 04:42 -- 05:00 PM @ Darling Harbour Theatre
Accelerating Eulerian Fluid Simulation With Convolutional Networks
Jonathan Tompson · Kristofer D Schlachter · Pablo Sprechmann · Ken Perlin
Talk
Wed Aug 9th 04:42 -- 05:00 PM @ Parkside 2
Rule-Enhanced Penalized Regression by Column Generation using Rectangular Maximum Agreement
Jonathan Eckstein · Noam Goldberg · Ai Kagawa
Talk
Wed Aug 9th 04:42 -- 05:00 PM @ C4.9& C4.10
High Dimensional Bayesian Optimization with Elastic Gaussian Process
Santu Rana · Cheng Li · Sunil Gupta · Vu Nguyen · Svetha Venkatesh
Talk
Wed Aug 9th 04:42 -- 05:00 PM @ C4.8
Nyström Method with Kernel K-means++ Samples as Landmarks
Dino Oglic · Thomas Gaertner
Talk
Wed Aug 9th 04:42 -- 05:00 PM @ C4.6 & C4.7
Scalable Generative Models for Multi-label Learning with Missing Labels
Vikas Jain · Nirbhay Modhe · Piyush Rai
Invited Talk
Wed Aug 9th 05:15 -- 06:15 PM @ Darling Harbour Theatre
How AI Designers will Dictate Our Civic Future
Latanya Sweeney
Break
Wed Aug 9th 06:15 -- 08:00 PM @ Ballroom
Closing Reception
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #1
Sketched Ridge Regression: Optimization Perspective, Statistical Perspective, and Model Averaging
Shusen Wang · Alex Gittens · Michael Mahoney
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #2
Estimating the unseen from multiple populations
Aditi Raghunathan · Greg Valiant · James Zou
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #3
Meritocratic Fairness for Cross-Population Selection
Michael Kearns · Aaron Roth · Steven Wu
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #4
Neural networks and rational functions
Matus Telgarsky
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #5
Input Convex Neural Networks
Brandon Amos · Lei Xu · Zico Kolter
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #6
Co-clustering through Optimal Transport
Charlotte Laclau · Ievgen Redko · Basarab Matei · Younès Bennani · Vincent Brault
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #7
OptNet: Differentiable Optimization as a Layer in Neural Networks
Brandon Amos · Zico Kolter
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #8
Multiple Clustering Views from Multiple Uncertain Experts
Yale Chang · Junxiang Chen · Michael Cho · Peter Castaldi · Edwin Silverman · Jennifer G Dy
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #9
Parseval Networks: Improving Robustness to Adversarial Examples
Moustapha Cisse · Piotr Bojanowski · Edouard Grave · Yann Dauphin · Nicolas Usunier
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #10
Clustering by Sum of Norms: Stochastic Incremental Algorithm, Convergence and Cluster Recovery
Ashkan Panahi · Devdatt Dubhashi · Fredrik D Johansson · Chiranjib Bhattacharya
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #11
Regularising Non-linear Models Using Feature Side-information
Amina Mollaysa · Pablo Strasser · Alexandros Kalousis
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #12
Clustering High Dimensional Dynamic Data Streams
Lin Yang · Harry Lang · Christian Sohler · Vladimir Braverman · Gereon Frahling
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #13
Fast k-Nearest Neighbour Search via Prioritized DCI
Ke Li · Jitendra Malik
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #14
Deep Spectral Clustering Learning
Marc Law · Raquel Urtasun · Zemel Rich
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #15
Joint Dimensionality Reduction and Metric Learning: A Geometric Take
Mehrtash Harandi · Mathieu Salzmann · Richard I Hartley
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #16
ProtoNN: Compressed and Accurate kNN for Resource-scarce Devices
Chirag Gupta · ARUN SUGGALA · Ankit Goyal · Saurabh Goyal · Ashish Kumar · Bhargavi Paranjape · Harsha Vardhan Simhadri · Raghavendra Udupa · Manik Varma · Prateek Jain
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #17
Device Placement Optimization with Reinforcement Learning
Azalia Mirhoseini · Hieu Pham · Quoc Le · benoit steiner · Mohammad Norouzi · Rasmus Larsen · Yuefeng Zhou · Naveen Kumar · Samy Bengio · Jeff Dean
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #18
Dynamic Word Embeddings
Robert Bamler · Stephan Mandt
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #19
Asynchronous Stochastic Gradient Descent with Delay Compensation
Shuxin Zheng · Qi Meng · Taifeng Wang · Wei Chen · Nenghai Yu · Zhiming Ma · Tie-Yan Liu
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #20
Improving Stochastic Policy Gradients in Continuous Control with Deep Reinforcement Learning using the Beta Distribution
Po-Wei Chou · Daniel Maturana · Sebastian Scherer
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #21
Fractional Langevin Monte Carlo: Exploring Levy Driven Stochastic Differential Equations for MCMC
Umut Simsekli
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #22
Preferential Bayesian Optmization
Javier González · Zhenwen Dai · Andreas Damianou · Neil Lawrence
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #23
Being Robust (in High Dimensions) Can Be Practical
Ilias Diakonikolas · Gautam Kamath · Daniel Kane · Jerry Li · Ankur Moitra · Alistair Stewart
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #24
Differentially Private Ordinary Least Squares
Or Sheffet
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #25
When can Multi-Site Datasets be Pooled for Regression? Hypothesis Tests, $\ell_2$-consistency and Neuroscience Applications
Hao Zhou · Yilin Zhang · Vamsi Ithapu · Sterling Johnson · Grace Wahba · Vikas Singh
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #26
Deep Tensor Convolution on Multicores
David Budden · Alexander Matveev · Shibani Santurkar · Shraman Ray Chaudhuri · Nir Shavit
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #27
Gram-CTC: Automatic Unit Selection and Target Decomposition for Sequence Labelling
Hairong Liu · Zhenyao Zhu · Xiangang Li · Sanjeev Satheesh
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #28
Adaptive Consensus ADMM for Distributed Optimization
Zheng Xu · Gavin Taylor · Hao Li · Mario Figueiredo · Xiaoming Yuan · Tom Goldstein
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #29
Combining Model-Based and Model-Free Updates for Trajectory-Centric Reinforcement Learning
Yevgen Chebotar · Karol Hausman · Marvin Zhang · Gaurav Sukhatme · Stefan Schaal · Sergey Levine
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #30
Stochastic Bouncy Particle Sampler
Ari Pakman · Dar Gilboa · David Carlson · Liam Paninski
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #31
Max-value Entropy Search for Efficient Bayesian Optimization
Zi Wang · Stefanie Jegelka
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #32
Multilabel Classification with Group Testing and Codes
Shashanka Ubaru · Arya Mazumdar
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #33
Priv’IT: Private and Sample Efficient Identity Testing
Bryan Cai · Constantinos Daskalakis · Gautam Kamath
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #34
Learning from Clinical Judgments: Semi-Markov-Modulated Marked Hawkes Processes for Risk Prognosis
Ahmed M. Alaa Ibrahim · Scott B Hu · Mihaela van der Schaar
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #35
MEC: Memory-efficient Convolution for Deep Neural Network
Minsik Cho · Daniel Brand
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #36
Coupling Distributed and Symbolic Execution for Natural Language Queries
Lili Mou · Zhengdong Lu · Hang Li · Zhi Jin
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #37
Optimal Algorithms for Smooth and Strongly Convex Distributed Optimization in Networks
Kevin Scaman · Francis Bach · Sebastien Bubeck · Yin Tat Lee · Laurent Massoulié
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #38
Prediction under Uncertainty in Sparse Spectrum Gaussian Processes with Applications to Filtering and Control
Yunpeng Pan · Xinyan Yan · Evangelos Theodorou · Byron Boots
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #39
Canopy --- Fast Sampling with Cover Trees
Manzil Zaheer · Satwik Kottur · Amr Ahmed · Jose Moura · Alex Smola
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #40
Bayesian Optimization with Tree-structured Dependencies
Rodolphe Jenatton · Cedric Archambeau · Javier González · Matthias Seeger
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #41
High-Dimensional Structured Quantile Regression
Vidyashankar Sivakumar · Arindam Banerjee
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #42
Differentially Private Submodular Maximization: Data Summarization in Disguise
Marko Mitrovic · Mark Bun · Andreas Krause · Amin Karbasi
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #43
Learning to Detect Sepsis with a Multitask Gaussian Process RNN Classifier
Joseph Futoma · Sanjay Hariharan · Katherine Heller
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #44
Beyond Filters: Compact Feature Map for Portable Deep Model
Yunhe Wang · Chang Xu · Chao Xu · Dacheng Tao
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #45
Image-to-Markup Generation with Coarse-to-Fine Attention
Yuntian Deng · Anssi Kanervisto · Jeffrey Ling · Alexander Rush
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #46
Projection-free Distributed Online Learning in Networks
Wenpeng Zhang · Peilin Zhao · wenwu zhu · Steven Hoi · Tong Zhang
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #47
Learning Stable Stochastic Nonlinear Dynamical Systems
Jonas Umlauft · Sandra Hirche
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #48
A Simulated Annealing Based Inexact Oracle for Wasserstein Loss Minimization
Jianbo Ye · James Wang · Jia Li
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #49
Multi-fidelity Bayesian Optimisation with Continuous Approximations
kirthevasan kandasamy · Gautam Dasarathy · Barnabás Póczos · Jeff Schneider
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #50
High-dimensional Non-Gaussian Single Index Models via Thresholded Score Function Estimation
Zhuoran Yang · Krishnakumar Balasubramanian · Han Liu
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #51
Differentially Private Learning of Graphical Models using CGMs
Garrett Bernstein · Ryan McKenna · Tao Sun · Daniel Sheldon · Michael Hay · Gerome Miklau
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #52
iSurvive: An Interpretable, Event-time Prediction Model for mHealth
Walter Dempsey · Alexander Moreno · Jim Rehg · Susan Murphy · Chris Scott · Michael Dennis · David Gustafson
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #53
Efficient softmax approximation for GPUs
Edouard Grave · Armand Joulin · Moustapha Cisse · David Grangier · Herve Jegou
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #54
Multichannel End-to-end Speech Recognition
Tsubasa Ochiai · Shinji Watanabe · Takaaki Hori · John Hershey
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #55
Local Bayesian Optimization of Motor Skills
Riadh Akrour · Dmitry Sorokin · Jan Peters · Gerhard Neumann
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #56
Improving Gibbs Sampler Scan Quality with DoGS
Ioannis Mitliagkas · Lester Mackey
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #57
Parallel and Distributed Thompson Sampling for Large-scale Accelerated Exploration of Chemical Space
Jose Hernandez-Lobato · James Requeima · Edward Pyzer-Knapp · alan Aspuru-Guzik
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #58
Robust Structured Estimation with Single-Index Models
Sheng Chen · Arindam Banerjee
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #59
Minimizing Trust Leaks for Robust Sybil Detection
János Höner · Shinichi Nakajima · Alexander Bauer · Klaus-robert Mueller · Nico Görnitz
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #60
Learning Sleep Stages from Radio Signals: A Conditional Adversarial Architecture
Mingmin Zhao · Shichao Yue · Dina Katabi · Tommi Jaakkola · Matt Bianchi
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #61
Dropout Inference in Bayesian Neural Networks with Alpha-divergences
Yingzhen Li · Yarin Gal
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #62
Latent Intention Dialogue Models
Tsung-Hsien Wen · Yishu Miao · Phil Blunsom · Stephen J Young
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #63
Robust Guarantees of Stochastic Greedy Algorithms
Yaron Singer · Avinatan Hassidim
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #64
Count-Based Exploration with Neural Density Models
Georg Ostrovski · Marc Bellemare · Aäron van den Oord · Remi Munos
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #65
Magnetic Hamiltonian Monte Carlo
Nilesh Tripuraneni · Mark Rowland · Zoubin Ghahramani · Richard E Turner
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #66
Uncertainty Assessment and False Discovery Rate Control in High-Dimensional Granger Causal Inference
Aditya Chaudhry · Pan Xu · Quanquan Gu
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #67
Toward Efficient and Accurate Covariance Matrix Estimation on Compressed Data
Xixian Chen · Michael Lyu · Irwin King
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #68
The Price of Differential Privacy For Online Learning
Naman Agarwal · Karan Singh
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #69
Bidirectional learning for time-series models with hidden units
Takayuki Osogami · Hiroshi Kajino · Taro Sekiyama
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #70
Multiplicative Normalizing Flows for Variational Bayesian Neural Networks
Christos Louizos · Max Welling
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #71
Discovering Discrete Latent Topics with Neural Variational Inference
Yishu Miao · Edward Grefenstette · Phil Blunsom
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #72
Guarantees for Greedy Maximization of Non-submodular Functions with Applications
Andrew An Bian · Joachim Buhmann · Andreas Krause · Sebastian Tschiatschek
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #73
Zero-Shot Task Generalization with Multi-Task Deep Reinforcement Learning
Junhyuk Oh · Satinder Singh · Honglak Lee · Pushmeet Kohli
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #74
Probabilistic Path Hamiltonian Monte Carlo
Vu Dinh · Arman Bilge · Cheng Zhang · Frederick Matsen
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #75
Uncovering Causality from Multivariate Hawkes Integrated Cumulants
Massil Achab · Emmanuel Bacry · Stéphane Gaïffas · Iacopo Mastromatteo · Jean-François Muzy
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #76
Robust Gaussian Graphical Model Estimation with Arbitrary Corruption
Lingxiao Wang · Quanquan Gu
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #77
Pain-Free Random Differential Privacy with Sensitivity Sampling
Benjamin Rubinstein · Francesco Aldà
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #78
Learning Hawkes Processes from Short Doubly-Censored Event Sequences
Hongteng Xu · Dixin Luo · Hongyuan Zha
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #79
Variational Dropout Sparsifies Deep Neural Networks
Dmitry Molchanov · Arsenii Ashukha · Dmitry Vetrov
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #80
Toward Controlled Generation of Text
Zhiting Hu · Zichao Yang · Xiaodan Liang · Ruslan Salakhutdinov · Eric Xing
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #81
Robust Submodular Maximization: A Non-Uniform Partitioning Approach
Ilija Bogunovic · Slobodan Mitrovic · Jonathan Scarlett · Volkan Cevher
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #82
Stabilising Experience Replay for Deep Multi-Agent Reinforcement Learning
Jakob Foerster · Nantas Nardelli · Gregory Farquhar · Triantafyllos Afouras · Phil Torr · Pushmeet Kohli · Shimon Whiteson
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #83
Stochastic Gradient Monomial Gamma Sampler
Yizhe Zhang · Changyou Chen · Zhe Gan · Ricardo Henao · Lawrence Carin
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #84
Cost-Optimal Learning of Causal Graphs
Murat Kocaoglu · Alexandros Dimakis · Sriram Vishwanath
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #85
Algebraic Variety Models for High-Rank Matrix Completion
Greg Ongie · Laura Balzano · Rebecca Willett · Robert Nowak
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #86
Differentially Private Clustering in High-Dimensional Euclidean Spaces
Nina Balcan · Travis Dick · Yingyu Liang · Wenlong Mou · Hongyang Zhang
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #87
Coherent probabilistic forecasts for hierarchical time series
Souhaib Ben Taieb · James Taylor · Rob Hyndman
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #88
Unimodal Probability Distributions for Deep Ordinal Classification
Christopher Beckham · Christopher Pal
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #89
Adversarial Feature Matching for Text Generation
Yizhe Zhang · Zhe Gan · Kai Fan · Zhi Chen · Ricardo Henao · Dinghan Shen · Lawrence Carin
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #90
Probabilistic Submodular Maximization in Sub-Linear Time
Serban A Stan · Morteza Zadimoghaddam · Andreas Krause · Amin Karbasi
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #91
The Predictron: End-To-End Learning and Planning
David Silver · Hado van Hasselt · Matteo Hessel · Tom Schaul · Arthur Guez · Tim Harley · Gabriel Dulac-Arnold · David Reichert · Neil Rabinowitz · Andre Barreto · Thomas Degris
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #92
Stochastic Gradient MCMC Methods for Hidden Markov Models
Yi-An Ma · Nicholas J Foti · Emily Fox
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #93
Identification and Model Testing in Linear Structural Equation Models using Auxiliary Variables
Bryant Chen · Daniel Kumor · Elias Bareinboim
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #94
High-Dimensional Variance-Reduced Stochastic Gradient Expectation-Maximization Algorithm
Rongda Zhu · Lingxiao Wang · Chengxiang Zhai · Quanquan Gu
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #95
Differentially Private Chi-squared Test by Unit Circle Mechanism
Kazuya Kakizaki · Kazuto Fukuchi · Jun Sakuma
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #96
Soft-DTW: a Differentiable Loss Function for Time-Series
Marco Cuturi · Mathieu Blondel
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #97
Learning Continuous Semantic Representations of Symbolic Expressions
Miltiadis Allamanis · pankajan Chanthirasegaran · Pushmeet Kohli · Charles Sutton
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #98
On Approximation Guarantees for Greedy Low Rank Optimization
RAJIV KHANNA · Ethan Elenberg · Alexandros Dimakis · Joydeep Ghosh · Sahand Negahban
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #99
Averaged-DQN: Variance Reduction and Stabilization for Deep Reinforcement Learning
Oron Anschel · Nir Baram · Nahum Shimkin
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #100
Deep Latent Dirichlet Allocation with Topic-Layer-Adaptive Stochastic Gradient Riemannian MCMC
Yulai Cong · Bo Chen · Hongwei Liu · Mingyuan Zhou
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #101
Estimating individual treatment effect: generalization bounds and algorithms
Uri Shalit · Fredrik D Johansson · David Sontag
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #102
Collect at Once, Use Effectively: Making Non-interactive Locally Private Learning Possible
Kai Zheng · Wenlong Mou · Liwei Wang
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #103
Variational Policy for Guiding Point Processes
Yichen Wang · Grady Williams · Evangelos Theodorou · Le Song
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #104
Dance Dance Convolution
Christopher Donahue · Zachary Lipton · Julian McAuley
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #105
Language Modeling with Gated Convolutional Networks
Yann Dauphin · Angela Fan · Michael Auli · David Grangier
Poster
Wed Aug 9th 06:30 -- 10:00 PM @ Gallery #106
Deletion-Robust Submodular Maximization: Data Summarization with "the Right to be Forgotten"
Baharan Mirzasoleiman · Amin Karbasi · Andreas Krause