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Thirtieth Conference on Neural Information Processing Systems Year (2016) 2020



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Log Out Contact NeurIPS Sponsor Info Publications Future Meetings Video Archives Diversity & Inclusion New in ML Code of Conduct About Us Press Board 2020 NIPS 2016 Accepted Papers

This accepted papers list has been superseded. Click here for the new list Scan Order in Gibbs Sampling: Models in Which it Matters and Bounds on How Much

Bryan He*, Stanford University; Christopher De Sa, Stanford University; Ioannis Mitliagkas, ; Christopher Ré, Stanford University



Bryan He*, Stanford University; Christopher De Sa, Stanford University; Ioannis Mitliagkas, ; Christopher Ré, Stanford University Deep ADMM-Net for Compressive Sensing MRI

Yan Yang, Xi'an Jiaotong University; Jian Sun*, Xi'an Jiaotong University; Huibin Li, ; Zongben Xu,



Yan Yang, Xi'an Jiaotong University; Jian Sun*, Xi'an Jiaotong University; Huibin Li, ; Zongben Xu, A scaled Bregman theorem with applications

Richard NOCK, Data61 and ANU; Aditya Menon*, ; Cheng Soon Ong, Data61



Richard NOCK, Data61 and ANU; Aditya Menon*, ; Cheng Soon Ong, Data61 Swapout: Learning an ensemble of deep architectures

Saurabh Singh*, UIUC; Derek Hoiem, UIUC; David Forsyth, UIUC



Saurabh Singh*, UIUC; Derek Hoiem, UIUC; David Forsyth, UIUC On Regularizing Rademacher Observation Losses

Richard NOCK*, Data61 and ANU



Richard NOCK*, Data61 and ANU Without-Replacement Sampling for Stochastic Gradient Methods

Ohad Shamir*, Weizmann Institute of Science



Ohad Shamir*, Weizmann Institute of Science Fast and Provably Good Seedings for k-Means

Olivier Bachem*, ETH Zurich; Mario Lucic, ETH Zurich; Hamed Hassani, ETH Zurich; Andreas Krause,



Olivier Bachem*, ETH Zurich; Mario Lucic, ETH Zurich; Hamed Hassani, ETH Zurich; Andreas Krause, Unsupervised Learning for Physical Interaction through Video Prediction

Chelsea Finn*, Google, Inc.; Ian Goodfellow, ; Sergey Levine, University of Washington



Chelsea Finn*, Google, Inc.; Ian Goodfellow, ; Sergey Levine, University of Washington Matrix Completion and Clustering in Self-Expressive Models

Ehsan Elhamifar*,



Ehsan Elhamifar*, Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial Modeling

Chengkai Zhang, ; Jiajun Wu*, MIT; Tianfan Xue, ; William Freeman, ; Joshua Tenenbaum,



Chengkai Zhang, ; Jiajun Wu*, MIT; Tianfan Xue, ; William Freeman, ; Joshua Tenenbaum, Probabilistic Modeling of Future Frames from a Single Image

Tianfan Xue*, ; Jiajun Wu, MIT; Katherine Bouman, MIT; William Freeman,



Tianfan Xue*, ; Jiajun Wu, MIT; Katherine Bouman, MIT; William Freeman, Human Decision-Making under Limited Time

Pedro Ortega*, ; Alan Stocker,



Pedro Ortega*, ; Alan Stocker, Incremental Boosting Convolutional Neural Network for Facial Action Unit Recognition

Shizhong Han*, University of South Carolina; Zibo Meng, University of South Carolina; Ahmed Shehab Khan, University of South Carolina; Yan Tong, University of South Carolina



Shizhong Han*, University of South Carolina; Zibo Meng, University of South Carolina; Ahmed Shehab Khan, University of South Carolina; Yan Tong, University of South Carolina Natural-Parameter Networks: A Class of Probabilistic Neural Networks

Hao Wang*, HKUST; Xingjian Shi, ; Dit-Yan Yeung,



Hao Wang*, HKUST; Xingjian Shi, ; Dit-Yan Yeung, Tree-Structured Reinforcement Learning for Sequential Object Localization

Zequn Jie*, National Univ of Singapore; Xiaodan Liang, Sun Yat-sen University; Jiashi Feng, National University of Singapo; Xiaojie Jin, NUS; Wen Feng Lu, National Univ of Singapore; Shuicheng Yan,



Zequn Jie*, National Univ of Singapore; Xiaodan Liang, Sun Yat-sen University; Jiashi Feng, National University of Singapo; Xiaojie Jin, NUS; Wen Feng Lu, National Univ of Singapore; Shuicheng Yan, Unsupervised Domain Adaptation with Residual Transfer Networks

Mingsheng Long*, Tsinghua University; Han Zhu, Tsinghua University; Jianmin Wang, Tsinghua University; Michael Jordan,



Mingsheng Long*, Tsinghua University; Han Zhu, Tsinghua University; Jianmin Wang, Tsinghua University; Michael Jordan, Verification Based Solution for Structured MAB Problems

Zohar Karnin*,



Zohar Karnin*, Minimizing Regret on Reflexive Banach Spaces and Nash Equilibria in Continuous Zero-Sum Games

Maximilian Balandat*, UC Berkeley; Walid Krichene, UC Berkeley; Claire Tomlin, UC Berkeley; Alexandre Bayen, UC Berkeley



Maximilian Balandat*, UC Berkeley; Walid Krichene, UC Berkeley; Claire Tomlin, UC Berkeley; Alexandre Bayen, UC Berkeley Linear dynamical neural population models through nonlinear embeddings

Yuanjun Gao, Columbia University; Evan Archer*, ; John Cunningham, ; Liam Paninski,



Yuanjun Gao, Columbia University; Evan Archer*, ; John Cunningham, ; Liam Paninski, SURGE: Surface Regularized Geometry Estimation from a Single Image

Peng Wang*, UCLA; Xiaohui Shen, Adobe Research; Bryan Russell, ; Scott Cohen, Adobe Research; Brian Price, ; Alan Yuille,



Peng Wang*, UCLA; Xiaohui Shen, Adobe Research; Bryan Russell, ; Scott Cohen, Adobe Research; Brian Price, ; Alan Yuille, Interpretable Distribution Features with Maximum Testing Power

Wittawat Jitkrittum*, Gatsby Unit, UCL; Zoltan Szabo, ; Kacper Chwialkowski, Gatsby Unit, UCL; Arthur Gretton,



Wittawat Jitkrittum*, Gatsby Unit, UCL; Zoltan Szabo, ; Kacper Chwialkowski, Gatsby Unit, UCL; Arthur Gretton, Sorting out typicality with the inverse moment matrix SOS polynomial

Edouard Pauwels*, ; Jean-Bernard Lasserre, LAAS-CNRS



Edouard Pauwels*, ; Jean-Bernard Lasserre, LAAS-CNRS Multi-armed Bandits: Competing with Optimal Sequences

Zohar Karnin*, ; Oren Anava, Technion



Zohar Karnin*, ; Oren Anava, Technion Multivariate tests of association based on univariate tests

Ruth Heller*, Tel-Aviv University; Yair Heller,



Ruth Heller*, Tel-Aviv University; Yair Heller, Learning What and Where to Draw

Scott Reed*, University of Michigan; Zeynep Akata, Max Planck Institute for Informatics; Santosh Mohan, University of MIchigan; Samuel Tenka, University of MIchigan; Bernt Schiele, ; Honglak Lee, University of Michigan



Scott Reed*, University of Michigan; Zeynep Akata, Max Planck Institute for Informatics; Santosh Mohan, University of MIchigan; Samuel Tenka, University of MIchigan; Bernt Schiele, ; Honglak Lee, University of Michigan The Sound of APALM Clapping: Faster Nonsmooth Nonconvex Optimization with Stochastic Asynchronous PALM

Damek Davis*, Cornell University; Brent Edmunds, University of California, Los Angeles; Madeleine Udell,



Damek Davis*, Cornell University; Brent Edmunds, University of California, Los Angeles; Madeleine Udell, Integrator Nets

Hakan Bilen*, University of Oxford; Andrea Vedaldi,



Hakan Bilen*, University of Oxford; Andrea Vedaldi, Combining Low-Density Separators with CNNs

Yu-Xiong Wang*, Carnegie Mellon University; Martial Hebert, Carnegie Mellon University



Yu-Xiong Wang*, Carnegie Mellon University; Martial Hebert, Carnegie Mellon University CNNpack: Packing Convolutional Neural Networks in the Frequency Domain

Yunhe Wang*, Peking University ; Shan You, ; Dacheng Tao, ; Chao Xu, ; Chang Xu,



Yunhe Wang*, Peking University ; Shan You, ; Dacheng Tao, ; Chao Xu, ; Chang Xu, Cooperative Graphical Models

Josip Djolonga*, ETH Zurich; Stefanie Jegelka, MIT; Sebastian Tschiatschek, ETH Zurich; Andreas Krause,



Josip Djolonga*, ETH Zurich; Stefanie Jegelka, MIT; Sebastian Tschiatschek, ETH Zurich; Andreas Krause, f-GAN: Training Generative Neural Samplers using Variational Divergence Minimization

Sebastian Nowozin*, Microsoft Research; Botond Cseke, Microsoft Research; Ryota Tomioka, MSRC



Sebastian Nowozin*, Microsoft Research; Botond Cseke, Microsoft Research; Ryota Tomioka, MSRC Bayesian Optimization for Probabilistic Programs

Tom Rainforth*, University of Oxford; Tuan Anh Le, University of Oxford; Jan-Willem van de Meent, University of Oxford; Michael Osborne, ; Frank Wood,



Tom Rainforth*, University of Oxford; Tuan Anh Le, University of Oxford; Jan-Willem van de Meent, University of Oxford; Michael Osborne, ; Frank Wood, Hierarchical Question-Image Co-Attention for Visual Question Answering

Jiasen Lu*, Virginia Tech; Jianwei Yang, Virginia Tech; Dhruv Batra, ; Devi Parikh, Virginia Tech



Jiasen Lu*, Virginia Tech; Jianwei Yang, Virginia Tech; Dhruv Batra, ; Devi Parikh, Virginia Tech Optimal Sparse Linear Encoders and Sparse PCA

Malik Magdon-Ismail*, Rensselaer; Christos Boutsidis,



Malik Magdon-Ismail*, Rensselaer; Christos Boutsidis, FPNN: Field Probing Neural Networks for 3D Data

Yangyan Li*, Stanford University; Soeren Pirk, Stanford University; Hao Su, Stanford University; Charles Qi, Stanford University; Leonidas Guibas, Stanford University



Yangyan Li*, Stanford University; Soeren Pirk, Stanford University; Hao Su, Stanford University; Charles Qi, Stanford University; Leonidas Guibas, Stanford University CRF-CNN: Modeling Structured Information in Human Pose Estimation

Xiao Chu*, Cuhk; Wanli Ouyang, ; hongsheng Li, cuhk; Xiaogang Wang, Chinese University of Hong Kong



Xiao Chu*, Cuhk; Wanli Ouyang, ; hongsheng Li, cuhk; Xiaogang Wang, Chinese University of Hong Kong Fairness in Learning: Classic and Contextual Bandits

Matthew Joseph, University of Pennsylvania; Michael Kearns, ; Jamie Morgenstern*, University of Pennsylvania; Aaron Roth,



Matthew Joseph, University of Pennsylvania; Michael Kearns, ; Jamie Morgenstern*, University of Pennsylvania; Aaron Roth, Joint M-Best-Diverse Labelings as a Parametric Submodular Minimization

Alexander Kirillov*, TU Dresden; Alexander Shekhovtsov, ; Carsten Rother, ; Bogdan Savchynskyy,



Alexander Kirillov*, TU Dresden; Alexander Shekhovtsov, ; Carsten Rother, ; Bogdan Savchynskyy, Domain Separation Networks

Dilip Krishnan, Google; George Trigeorgis, Google; Konstantinos Bousmalis*, ; Nathan Silberman, Google; Dumitru Erhan, Google



Dilip Krishnan, Google; George Trigeorgis, Google; Konstantinos Bousmalis*, ; Nathan Silberman, Google; Dumitru Erhan, Google DISCO Nets : DISsimilarity COefficients Networks

Diane Bouchacourt*, University of Oxford; M. Pawan Kumar, University of Oxford; Sebastian Nowozin,



Diane Bouchacourt*, University of Oxford; M. Pawan Kumar, University of Oxford; Sebastian Nowozin, Multimodal Residual Learning for Visual QA

Jin-Hwa Kim*, Seoul National University; Sang-Woo Lee, Seoul National University; Dong-Hyun Kwak, Seoul National University; Min-Oh Heo, Seoul National University; Jeonghee Kim, Naver Labs; Jung-Woo Ha, Naver Labs; Byoung-Tak Zhang, Seoul National University



Jin-Hwa Kim*, Seoul National University; Sang-Woo Lee, Seoul National University; Dong-Hyun Kwak, Seoul National University; Min-Oh Heo, Seoul National University; Jeonghee Kim, Naver Labs; Jung-Woo Ha, Naver Labs; Byoung-Tak Zhang, Seoul National University CMA-ES with Optimal Covariance Update and Storage Complexity

Dídac Rodríguez Arbonès, University of Copenhagen; Oswin Krause, ; Christian Igel*,



Dídac Rodríguez Arbonès, University of Copenhagen; Oswin Krause, ; Christian Igel*, R-FCN: Object Detection via Region-based Fully Convolutional Networks

Jifeng Dai, Microsoft; Yi Li, Tsinghua University; Kaiming He*, Microsoft; Jian Sun, Microsoft



Jifeng Dai, Microsoft; Yi Li, Tsinghua University; Kaiming He*, Microsoft; Jian Sun, Microsoft GAP Safe Screening Rules for Sparse-Group Lasso

Eugene Ndiaye, Télécom ParisTech; Olivier Fercoq, ; Alexandre Gramfort, ; Joseph Salmon*,



Eugene Ndiaye, Télécom ParisTech; Olivier Fercoq, ; Alexandre Gramfort, ; Joseph Salmon*, Learning and Forecasting Opinion Dynamics in Social Networks

Abir De, IIT Kharagpur; Isabel Valera, ; Niloy Ganguly, IIT Kharagpur; sourangshu Bhattacharya, IIT Kharagpur; Manuel Gomez Rodriguez*, MPI-SWS



Abir De, IIT Kharagpur; Isabel Valera, ; Niloy Ganguly, IIT Kharagpur; sourangshu Bhattacharya, IIT Kharagpur; Manuel Gomez Rodriguez*, MPI-SWS Gradient-based Sampling: An Adaptive Importance Sampling for Least-squares

Rong Zhu*, Chinese Academy of Sciences



Rong Zhu*, Chinese Academy of Sciences Collaborative Recurrent Autoencoder: Recommend while Learning to Fill in the Blanks

Hao Wang*, HKUST; Xingjian Shi, ; Dit-Yan Yeung,



Hao Wang*, HKUST; Xingjian Shi, ; Dit-Yan Yeung, Mutual information for symmetric rank-one matrix estimation: A proof of the replica formula

Jean Barbier, EPFL; mohamad Dia, EPFL; Florent Krzakala*, ; Thibault Lesieur, IPHT Saclay; Nicolas Macris, EPFL; Lenka Zdeborova,



Jean Barbier, EPFL; mohamad Dia, EPFL; Florent Krzakala*, ; Thibault Lesieur, IPHT Saclay; Nicolas Macris, EPFL; Lenka Zdeborova, A Unified Approach for Learning the Parameters of Sum-Product Networks

Han Zhao*, Carnegie Mellon University; Pascal Poupart, ; Geoff Gordon,



Han Zhao*, Carnegie Mellon University; Pascal Poupart, ; Geoff Gordon, Training and Evaluating Multimodal Word Embeddings with Large-scale Web Annotated Images

Junhua Mao*, UCLA; Jiajing Xu, ; Kevin Jing, ; Alan Yuille,



Junhua Mao*, UCLA; Jiajing Xu, ; Kevin Jing, ; Alan Yuille, Stochastic Online AUC Maximization

Yiming Ying*, ; Longyin Wen, State University of New York at Albany; Siwei Lyu, State University of New York at Albany



Yiming Ying*, ; Longyin Wen, State University of New York at Albany; Siwei Lyu, State University of New York at Albany The Generalized Reparameterization Gradient

Francisco Ruiz*, Columbia University; Michalis K. Titsias, ; David Blei,



Francisco Ruiz*, Columbia University; Michalis K. Titsias, ; David Blei, Coupled Generative Adversarial Networks

Ming-Yu Liu*, MERL; Oncel Tuzel, Mitsubishi Electric Research Labs (MERL)



Ming-Yu Liu*, MERL; Oncel Tuzel, Mitsubishi Electric Research Labs (MERL) Exponential Family Embeddings

Maja Rudolph*, Columbia University; Francisco J. R. Ruiz, ; Stephan Mandt, Disney Research; David Blei,



Maja Rudolph*, Columbia University; Francisco J. R. Ruiz, ; Stephan Mandt, Disney Research; David Blei, Variational Information Maximization for Feature Selection

Shuyang Gao*, ; Greg Ver Steeg, ; Aram Galstyan,



Shuyang Gao*, ; Greg Ver Steeg, ; Aram Galstyan, Operator Variational Inference

Rajesh Ranganath*, Princeton University; Dustin Tran, Columbia University; Jaan Altosaar, Princeton University; David Blei,



Rajesh Ranganath*, Princeton University; Dustin Tran, Columbia University; Jaan Altosaar, Princeton University; David Blei, Fast learning rates with heavy-tailed losses

Vu Dinh*, Fred Hutchinson Cancer Center; Lam Ho, UCLA; Binh Nguyen, University of Science, Vietnam; Duy Nguyen, University of Wisconsin-Madison



Vu Dinh*, Fred Hutchinson Cancer Center; Lam Ho, UCLA; Binh Nguyen, University of Science, Vietnam; Duy Nguyen, University of Wisconsin-Madison Budgeted stream-based active learning via adaptive submodular maximization

Kaito Fujii*, Kyoto University; Hisashi Kashima, Kyoto University



Kaito Fujii*, Kyoto University; Hisashi Kashima, Kyoto University Learning feed-forward one-shot learners

Luca Bertinetto, University of Oxford; Joao Henriques, University of Oxford; Jack Valmadre*, University of Oxford; Philip Torr, ; Andrea Vedaldi,



Luca Bertinetto, University of Oxford; Joao Henriques, University of Oxford; Jack Valmadre*, University of Oxford; Philip Torr, ; Andrea Vedaldi, Learning User Perceived Clusters with Feature-Level Supervision

Ting-Yu Cheng, ; Kuan-Hua Lin, ; Xinyang Gong, Baidu Inc.; Kang-Jun Liu, ; Shan-Hung Wu*, National Tsing Hua University



Ting-Yu Cheng, ; Kuan-Hua Lin, ; Xinyang Gong, Baidu Inc.; Kang-Jun Liu, ; Shan-Hung Wu*, National Tsing Hua University Robust Spectral Detection of Global Structures in the Data by Learning a Regularization

Pan Zhang*, ITP, CAS



Pan Zhang*, ITP, CAS Residual Networks are Exponential Ensembles of Relatively Shallow Networks

Andreas Veit*, Cornell University; Michael Wilber, ; Serge Belongie, Cornell University



Andreas Veit*, Cornell University; Michael Wilber, ; Serge Belongie, Cornell University Adversarial Multiclass Classification: A Risk Minimization Perspective

Rizal Fathony*, U. of Illinois at Chicago; Anqi Liu, ; Kaiser Asif, ; Brian Ziebart,



Rizal Fathony*, U. of Illinois at Chicago; Anqi Liu, ; Kaiser Asif, ; Brian Ziebart, Solving Random Systems of Quadratic Equations via Truncated Generalized Gradient Flow

Gang Wang*, University of Minnesota; Georgios Giannakis, University of Minnesota



Gang Wang*, University of Minnesota; Georgios Giannakis, University of Minnesota Coin Betting and Parameter-Free Online Learning

Francesco Orabona*, Yahoo Research; David Pal,



Francesco Orabona*, Yahoo Research; David Pal, Deep Learning without Poor Local Minima

Kenji Kawaguchi*, MIT



Kenji Kawaguchi*, MIT Testing for Differences in Gaussian Graphical Models: Applications to Brain Connectivity

Eugene Belilovsky*, CentraleSupelec; Gael Varoquaux, ; Matthew Blaschko, KU Leuven



Eugene Belilovsky*, CentraleSupelec; Gael Varoquaux, ; Matthew Blaschko, KU Leuven A Constant-Factor Bi-Criteria Approximation Guarantee for k-means++

Dennis Wei*, IBM Research



Dennis Wei*, IBM Research Generating Videos with Scene Dynamics

Carl Vondrick*, MIT; Hamed Pirsiavash, ; Antonio Torralba,



Carl Vondrick*, MIT; Hamed Pirsiavash, ; Antonio Torralba, Neurally-Guided Procedural Models: Amortized Inference for Procedural Graphics Programs

Daniel Ritchie*, Stanford University; Anna Thomas, Stanford University; Pat Hanrahan, Stanford University; Noah Goodman,



Daniel Ritchie*, Stanford University; Anna Thomas, Stanford University; Pat Hanrahan, Stanford University; Noah Goodman, A Powerful Generative Model Using Random Weights for the Deep Image Representation

Kun He, Huazhong University of Science and Technology; Yan Wang*, HUAZHONG UNIVERSITY OF SCIENCE; John Hopcroft, Cornell University



Kun He, Huazhong University of Science and Technology; Yan Wang*, HUAZHONG UNIVERSITY OF SCIENCE; John Hopcroft, Cornell University Optimizing affinity-based binary hashing using auxiliary coordinates

Ramin Raziperchikolaei, UC Merced; Miguel Carreira-Perpinan*, UC Merced



Ramin Raziperchikolaei, UC Merced; Miguel Carreira-Perpinan*, UC Merced Double Thompson Sampling for Dueling Bandits

Huasen Wu*, University of California at Davis; Xin Liu, University of California, Davis



Huasen Wu*, University of California at Davis; Xin Liu, University of California, Davis Generating Images with Perceptual Similarity Metrics based on Deep Networks

Alexey Dosovitskiy*, ; Thomas Brox, University of Freiburg



Alexey Dosovitskiy*, ; Thomas Brox, University of Freiburg Dynamic Filter Networks

Xu Jia*, KU Leuven; Bert De Brabandere, ; Tinne Tuytelaars, KU Leuven; Luc Van Gool, ETH Zürich



Xu Jia*, KU Leuven; Bert De Brabandere, ; Tinne Tuytelaars, KU Leuven; Luc Van Gool, ETH Zürich A Simple Practical Accelerated Method for Finite Sums

Aaron Defazio*, Ambiata



Aaron Defazio*, Ambiata Barzilai-Borwein Step Size for Stochastic Gradient Descent

Conghui Tan*, The Chinese University of HK; Shiqian Ma, ; Yu-Hong Dai, ; Yuqiu Qian, The University of Hong Kong



Conghui Tan*, The Chinese University of HK; Shiqian Ma, ; Yu-Hong Dai, ; Yuqiu Qian, The University of Hong Kong On Graph Reconstruction via Empirical Risk Minimization: Fast Learning Rates and Scalability

Guillaume Papa, Télécom ParisTech; Aurélien Bellet*, ; Stephan Clémencon,



Guillaume Papa, Télécom ParisTech; Aurélien Bellet*, ; Stephan Clémencon, Optimal spectral transportation with application to music transcription

Rémi Flamary, ; Cédric Févotte*, CNRS; Nicolas Courty, ; Valentin Emiya, Aix-Marseille University



Rémi Flamary, ; Cédric Févotte*, CNRS; Nicolas Courty, ; Valentin Emiya, Aix-Marseille University Regularized Nonlinear Acceleration

Damien Scieur*, INRIA - ENS; Alexandre D'Aspremont, ; Francis Bach,



Damien Scieur*, INRIA - ENS; Alexandre D'Aspremont, ; Francis Bach, SPALS: Fast Alternating Least Squares via Implicit Leverage Scores Sampling

Dehua Cheng*, Univ. of Southern California; Richard Peng, ; Yan Liu, ; Ioakeim Perros, Georgia Institute of Technology



Dehua Cheng*, Univ. of Southern California; Richard Peng, ; Yan Liu, ; Ioakeim Perros, Georgia Institute of Technology Single-Image Depth Perception in the Wild

Weifeng Chen*, University of Michigan; Zhao Fu, University of Michigan; Dawei Yang, University of Michigan; Jia Deng,



Weifeng Chen*, University of Michigan; Zhao Fu, University of Michigan; Dawei Yang, University of Michigan; Jia Deng, Computational and Statistical Tradeoffs in Learning to Rank

Ashish Khetan*, University of Illinois Urbana-; Sewoong Oh,



Ashish Khetan*, University of Illinois Urbana-; Sewoong Oh, Learning to Poke by Poking: Experiential Learning of Intuitive Physics

Pulkit Agrawal*, UC Berkeley; Ashvin Nair, UC Berkeley; Pieter Abbeel, ; Jitendra Malik, ; Sergey Levine, University of Washington



Pulkit Agrawal*, UC Berkeley; Ashvin Nair, UC Berkeley; Pieter Abbeel, ; Jitendra Malik, ; Sergey Levine, University of Washington Online Convex Optimization with Unconstrained Domains and Losses

Ashok Cutkosky*, Stanford University; Kwabena Boahen, Stanford University



Ashok Cutkosky*, Stanford University; Kwabena Boahen, Stanford University An ensemble diversity approach to supervised binary hashing

Miguel Carreira-Perpinan*, UC Merced; Ramin Raziperchikolaei, UC Merced



Miguel Carreira-Perpinan*, UC Merced; Ramin Raziperchikolaei, UC Merced Efficient Globally Convergent Stochastic Optimization for Canonical Correlation Analysis

Weiran Wang*, ; Jialei Wang, University of Chicago; Dan Garber, ; Nathan Srebro,



Weiran Wang*, ; Jialei Wang, University of Chicago; Dan Garber, ; Nathan Srebro, The Power of Adaptivity in Identifying Statistical Alternatives

Kevin Jamieson*, UC Berkeley; Daniel Haas, ; Ben Recht,



Kevin Jamieson*, UC Berkeley; Daniel Haas, ; Ben Recht, On Explore-Then-Commit strategies

Aurelien Garivier, ; Tor Lattimore, ; Emilie Kaufmann*,



Aurelien Garivier, ; Tor Lattimore, ; Emilie Kaufmann*, Sublinear Time Orthogonal Tensor Decomposition

Zhao Song*, UT-Austin; David Woodruff, ; Huan Zhang, UC-Davis



Zhao Song*, UT-Austin; David Woodruff, ; Huan Zhang, UC-Davis DECOrrelated feature space partitioning for distributed sparse regression

Xiangyu Wang*, Duke University; David Dunson, Duke University; Chenlei Leng, University of Warwick



Xiangyu Wang*, Duke University; David Dunson, Duke University; Chenlei Leng, University of Warwick Deep Alternative Neural Networks: Exploring Contexts as Early as Possible for Action Recognition

Jinzhuo Wang*, PKU; Wenmin Wang, peking university; xiongtao Chen, peking university; Ronggang Wang, peking university; Wen Gao, peking university



Jinzhuo Wang*, PKU; Wenmin Wang, peking university; xiongtao Chen, peking university; Ronggang Wang, peking university; Wen Gao, peking university Machine Translation Through Learning From a Communication Game

Di He*, Microsoft; Yingce Xia, USTC; Tao Qin, Microsoft; Liwei Wang, ; Nenghai Yu, USTC; Tie-Yan Liu, Microsoft; wei-Ying Ma, Microsoft



Di He*, Microsoft; Yingce Xia, USTC; Tao Qin, Microsoft; Liwei Wang, ; Nenghai Yu, USTC; Tie-Yan Liu, Microsoft; wei-Ying Ma, Microsoft Dialog-based Language Learning

Jason Weston*,



Jason Weston*, Joint Line Segmentation and Transcription for End-to-End Handwritten Paragraph Recognition

Theodore Bluche*, A2iA



Theodore Bluche*, A2iA Temporal Regularized Matrix Factorization for High-dimensional Time Series Prediction

Hsiang-Fu Yu*, University of Texas at Austin; Nikhil Rao, ; Inderjit Dhillon,



Hsiang-Fu Yu*, University of Texas at Austin; Nikhil Rao, ; Inderjit Dhillon, Active Nearest-Neighbor Learning in Metric Spaces

Aryeh Kontorovich, ; Sivan Sabato*, Ben-Gurion University of the Negev; Ruth Urner, MPI Tuebingen



Aryeh Kontorovich, ; Sivan Sabato*, Ben-Gurion University of the Negev; Ruth Urner, MPI Tuebingen Proximal Deep Structured Models

Shenlong Wang*, University of Toronto; Sanja Fidler, ; Raquel Urtasun,



Shenlong Wang*, University of Toronto; Sanja Fidler, ; Raquel Urtasun, Faster Projection-free Convex Optimization over the Spectrahedron

Dan Garber*,



Dan Garber*, Bayesian Optimization with a Finite Budget: An Approximate Dynamic Programming Approach

Remi Lam*, MIT; Karen Willcox, MIT; David Wolpert,



Remi Lam*, MIT; Karen Willcox, MIT; David Wolpert, Learning Sound Representations from Unlabeled Video

Yusuf Aytar, MIT; Carl Vondrick*, MIT; Antonio Torralba,



Yusuf Aytar, MIT; Carl Vondrick*, MIT; Antonio Torralba, Weight Normalization: A Simple Reparameterization to Accelerate Training of Deep Neural Networks

Tim Salimans*, ; Diederik Kingma,



Tim Salimans*, ; Diederik Kingma, Efficient Second Order Online Learning by Sketching

Haipeng Luo*, Princeton University; Alekh Agarwal, Microsoft; Nicolò Cesa-Bianchi, ; John Langford,



Haipeng Luo*, Princeton University; Alekh Agarwal, Microsoft; Nicolò Cesa-Bianchi, ; John Langford, Dynamic Mode Decomposition with Reproducing Kernels for Koopman Spectral Analysis

Yoshinobu Kawahara*, Osaka University



Yoshinobu Kawahara*, Osaka University Distributed Flexible Nonlinear Tensor Factorization

Shandian Zhe*, Purdue University; Kai Zhang, Lawrence Berkeley Lab; Pengyuan Wang, Yahoo! Research; Kuang-chih Lee, ; Zenglin Xu, ; Alan Qi, ; Zoubin Ghahramani,



Shandian Zhe*, Purdue University; Kai Zhang, Lawrence Berkeley Lab; Pengyuan Wang, Yahoo! Research; Kuang-chih Lee, ; Zenglin Xu, ; Alan Qi, ; Zoubin Ghahramani, The Robustness of Estimator Composition

Pingfan Tang*, University of Utah; Jeff Phillips, University of Utah



Pingfan Tang*, University of Utah; Jeff Phillips, University of Utah Efficient and Robust Spiking Neural Circuit for Navigation Inspired by Echolocating Bats

Bipin Rajendran*, NJIT; Pulkit Tandon, IIT Bombay; Yash Malviya, IIT Bombay



Bipin Rajendran*, NJIT; Pulkit Tandon, IIT Bombay; Yash Malviya, IIT Bombay PerforatedCNNs: Acceleration through Elimination of Redundant Convolutions

Michael Figurnov*, Skolkovo Inst. of Sc and Tech; Aijan Ibraimova, Skolkovo Institute of Science and Technology; Dmitry P. Vetrov, ; Pushmeet Kohli,



Michael Figurnov*, Skolkovo Inst. of Sc and Tech; Aijan Ibraimova, Skolkovo Institute of Science and Technology; Dmitry P. Vetrov, ; Pushmeet Kohli, Differential Privacy without Sensitivity

Kentaro Minami*, The University of Tokyo; HItomi Arai, The University of Tokyo; Issei Sato, The University of Tokyo; Hiroshi Nakagawa,



Kentaro Minami*, The University of Tokyo; HItomi Arai, The University of Tokyo; Issei Sato, The University of Tokyo; Hiroshi Nakagawa, Optimal Cluster Recovery in the Labeled Stochastic Block Model

Se-Young Yun*, Los Alamos National Laboratory; Alexandre Proutiere,



Se-Young Yun*, Los Alamos National Laboratory; Alexandre Proutiere, Even Faster SVD Decomposition Yet Without Agonizing Pain

Zeyuan Allen-Zhu*, Princeton University; Yuanzhi Li, Princeton University



Zeyuan Allen-Zhu*, Princeton University; Yuanzhi Li, Princeton University An algorithm for L1 nearest neighbor search via monotonic embedding

Xinan Wang*, UCSD; Sanjoy Dasgupta,



Xinan Wang*, UCSD; Sanjoy Dasgupta, Gaussian Process Bandit Optimisation with Multi-fidelity Evaluations

Kirthevasan Kandasamy*, CMU; Gautam Dasarathy, Carnegie Mellon University; Junier Oliva, ; Jeff Schneider, CMU; Barnabas Poczos,



Kirthevasan Kandasamy*, CMU; Gautam Dasarathy, Carnegie Mellon University; Junier Oliva, ; Jeff Schneider, CMU; Barnabas Poczos, Linear-Memory and Decomposition-Invariant Linearly Convergent Conditional Gradient Algorithm for Structured Polytopes

Dan Garber*, ; Ofer Meshi,



Dan Garber*, ; Ofer Meshi, Efficient Nonparametric Smoothness Estimation

Shashank Singh*, Carnegie Mellon University; Simon Du, Carnegie Mellon University; Barnabas Poczos,



Shashank Singh*, Carnegie Mellon University; Simon Du, Carnegie Mellon University; Barnabas Poczos, A Theoretically Grounded Application of Dropout in Recurrent Neural Networks

Yarin Gal*, University of Cambridge; Zoubin Ghahramani,



Yarin Gal*, University of Cambridge; Zoubin Ghahramani, Fast ε-free Inference of Simulation Models with Bayesian Conditional Density Estimation

George Papamakarios*, University of Edinburgh; Iain Murray, University of Edinburgh



George Papamakarios*, University of Edinburgh; Iain Murray, University of Edinburgh Direct Feedback Alignment Provides Learning In Deep Neural Networks

Arild Nøkland*, None



Arild Nøkland*, None Safe and Efficient Off-Policy Reinforcement Learning

Remi Munos, Google DeepMind; Thomas Stepleton, Google DeepMind; Anna Harutyunyan, Vrije Universiteit Brussel; Marc Bellemare*, Google DeepMind



Remi Munos, Google DeepMind; Thomas Stepleton, Google DeepMind; Anna Harutyunyan, Vrije Universiteit Brussel; Marc Bellemare*, Google DeepMind A Multi-Batch L-BFGS Method for Machine Learning

Albert Berahas*, Northwestern University; Jorge Nocedal, Northwestern University; Martin Takac, Lehigh University



Albert Berahas*, Northwestern University; Jorge Nocedal, Northwestern University; Martin Takac, Lehigh University Semiparametric Differential Graph Models

Pan Xu*, University of Virginia; Quanquan Gu, University of Virginia



Pan Xu*, University of Virginia; Quanquan Gu, University of Virginia Rényi Divergence Variational Inference

Yingzhen Li*, University of Cambridge; Richard E. Turner,



Yingzhen Li*, University of Cambridge; Richard E. Turner, Doubly Convolutional Neural Networks

Shuangfei Zhai*, Binghamton University; Yu Cheng, IBM Research; Zhongfei Zhang, Binghamton University



Shuangfei Zhai*, Binghamton University; Yu Cheng, IBM Research; Zhongfei Zhang, Binghamton University Density Estimation via Discrepancy Based Adaptive Sequential Partition

Dangna Li*, Stanford university; Kun Yang, Google Inc; Wing Wong, Stanford university



Dangna Li*, Stanford university; Kun Yang, Google Inc; Wing Wong, Stanford university How Deep is the Feature Analysis underlying Rapid Visual Categorization?

Sven Eberhardt*, Brown University; Jonah Cader, Brown University; Thomas Serre,



Sven Eberhardt*, Brown University; Jonah Cader, Brown University; Thomas Serre, Variational Information Maximizing Exploration

Rein Houthooft*, Ghent University - iMinds; UC Berkeley; OpenAI; Xi Chen, UC Berkeley; OpenAI; Yan Duan, UC Berkeley; John Schulman, OpenAI; Filip De Turck, Ghent University - iMinds; Pieter Abbeel,



Rein Houthooft*, Ghent University - iMinds; UC Berkeley; OpenAI; Xi Chen, UC Berkeley; OpenAI; Yan Duan, UC Berkeley; John Schulman, OpenAI; Filip De Turck, Ghent University - iMinds; Pieter Abbeel, Generalized Correspondence-LDA Models (GC-LDA) for Identifying Functional Regions in the Brain

Timothy Rubin*, Indiana University; Sanmi Koyejo, UIUC; Michael Jones, Indiana University; Tal Yarkoni, University of Texas at Austin



Timothy Rubin*, Indiana University; Sanmi Koyejo, UIUC; Michael Jones, Indiana University; Tal Yarkoni, University of Texas at Austin Solving Marginal MAP Problems with NP Oracles and Parity Constraints

Yexiang Xue*, Cornell University; Zhiyuan Li, Tsinghua University; Stefano Ermon, ; Carla Gomes, Cornell University; Bart Selman,



Yexiang Xue*, Cornell University; Zhiyuan Li, Tsinghua University; Stefano Ermon, ; Carla Gomes, Cornell University; Bart Selman, Multi-view Anomaly Detection via Robust Probabilistic Latent Variable Models

Tomoharu Iwata*, ; Makoto Yamada,



Tomoharu Iwata*, ; Makoto Yamada, Fast Stochastic Methods for Nonsmooth Nonconvex Optimization

Sashank Jakkam Reddi*, Carnegie Mellon University; Suvrit Sra, MIT; Barnabas Poczos, ; Alexander J. Smola,



Sashank Jakkam Reddi*, Carnegie Mellon University; Suvrit Sra, MIT; Barnabas Poczos, ; Alexander J. Smola, Variance Reduction in Stochastic Gradient Langevin Dynamics

Kumar Dubey*, Carnegie Mellon University; Sashank Jakkam Reddi, Carnegie Mellon University; Sinead Williamson, ; Barnabas Poczos, ; Alexander J. Smola, ; Eric Xing, Carnegie Mellon University



Kumar Dubey*, Carnegie Mellon University; Sashank Jakkam Reddi, Carnegie Mellon University; Sinead Williamson, ; Barnabas Poczos, ; Alexander J. Smola, ; Eric Xing, Carnegie Mellon University Regularization With Stochastic Transformations and Perturbations for Deep Semi-Supervised Learning

Mehdi Sajjadi*, University of Utah; Mehran Javanmardi, University of Utah; Tolga Tasdizen, University of Utah



Mehdi Sajjadi*, University of Utah; Mehran Javanmardi, University of Utah; Tolga Tasdizen, University of Utah Dense Associative Memory for Pattern Recognition

Dmitry Krotov*, Institute for Advanced Study; John Hopfield, Princeton Neuroscience Institute



Dmitry Krotov*, Institute for Advanced Study; John Hopfield, Princeton Neuroscience Institute Causal Bandits: Learning Good Interventions via Causal Inference

Finnian Lattimore, Australian National University; Tor Lattimore*, ; Mark Reid,



Finnian Lattimore, Australian National University; Tor Lattimore*, ; Mark Reid, Refined Lower Bounds for Adversarial Bandits

Sébastien Gerchinovitz, ; Tor Lattimore*,



Sébastien Gerchinovitz, ; Tor Lattimore*, Theoretical Comparisons of Positive-Unlabeled Learning against Positive-Negative Learning

Gang Niu*, University of Tokyo; Marthinus du Plessis, ; Tomoya Sakai, ; Yao Ma, ; Masashi Sugiyama, RIKEN / University of Tokyo



Gang Niu*, University of Tokyo; Marthinus du Plessis, ; Tomoya Sakai, ; Yao Ma, ; Masashi Sugiyama, RIKEN / University of Tokyo Homotopy Smoothing for Non-Smooth Problems with Lower Complexity than $O(1/\epsilon)$

Yi Xu*, The University of Iowa; Yan Yan, University of Technology Sydney; Qihang Lin, ; Tianbao Yang, University of Iowa



Yi Xu*, The University of Iowa; Yan Yan, University of Technology Sydney; Qihang Lin, ; Tianbao Yang, University of Iowa Finite-Sample Analysis of Fixed-k Nearest Neighbor Density Functionals Estimators

Shashank Singh*, Carnegie Mellon University; Barnabas Poczos,



Shashank Singh*, Carnegie Mellon University; Barnabas Poczos, A state-space model of cross-region dynamic connectivity in MEG/EEG

Ying Yang*, Carnegie Mellon University; Elissa Aminoff, Carnegie Mellon University; Michael Tarr, Carnegie Mellon University; Robert Kass, Carnegie Mellon University



Ying Yang*, Carnegie Mellon University; Elissa Aminoff, Carnegie Mellon University; Michael Tarr, Carnegie Mellon University; Robert Kass, Carnegie Mellon University What Makes Objects Similar: A Unified Multi-Metric Learning Approach

Han-Jia Ye, ; De-Chuan Zhan*, ; Xue-Min Si, Nanjing University; Yuan Jiang, Nanjing University; Zhi-Hua Zhou,



Han-Jia Ye, ; De-Chuan Zhan*, ; Xue-Min Si, Nanjing University; Yuan Jiang, Nanjing University; Zhi-Hua Zhou, Adaptive Maximization of Pointwise Submodular Functions With Budget Constraint

Nguyen Viet Cuong*, National University of Singapore; Huan Xu, NUS



Nguyen Viet Cuong*, National University of Singapore; Huan Xu, NUS Dueling Bandits: Beyond Condorcet Winners to General Tournament Solutions

Siddartha Ramamohan, Indian Institute of Science; Arun Rajkumar, ; Shivani Agarwal*, Radcliffe Institute, Harvard



Siddartha Ramamohan, Indian Institute of Science; Arun Rajkumar, ; Shivani Agarwal*, Radcliffe Institute, Harvard Local Similarity-Aware Deep Feature Embedding

Chen Huang*, Chinese University of HongKong; Chen Change Loy, The Chinese University of HK; Xiaoou Tang, The Chinese University of Hong Kong



Chen Huang*, Chinese University of HongKong; Chen Change Loy, The Chinese University of HK; Xiaoou Tang, The Chinese University of Hong Kong A Communication-Efficient Parallel Algorithm for Decision Tree

Qi Meng*, Peking University; Guolin Ke, Microsoft Research; Taifeng Wang, Microsoft Research; Wei Chen, Microsoft Research; Qiwei Ye, Microsoft Research; Zhi-Ming Ma, Academy of Mathematics and Systems Science, Chinese Academy of Sciences; Tie-Yan Liu, Microsoft Research



Qi Meng*, Peking University; Guolin Ke, Microsoft Research; Taifeng Wang, Microsoft Research; Wei Chen, Microsoft Research; Qiwei Ye, Microsoft Research; Zhi-Ming Ma, Academy of Mathematics and Systems Science, Chinese Academy of Sciences; Tie-Yan Liu, Microsoft Research Convex Two-Layer Modeling with Latent Structure

Vignesh Ganapathiraman, University Of Illinois at Chicago; Xinhua Zhang*, UIC; Yaoliang Yu, ; Junfeng Wen, UofA



Vignesh Ganapathiraman, University Of Illinois at Chicago; Xinhua Zhang*, UIC; Yaoliang Yu, ; Junfeng Wen, UofA Sampling for Bayesian Program Learning

Kevin Ellis*, MIT; Armando Solar-Lezama, MIT; Joshua Tenenbaum,



Kevin Ellis*, MIT; Armando Solar-Lezama, MIT; Joshua Tenenbaum, Learning Kernels with Random Features

Aman Sinha*, Stanford University; John Duchi,



Aman Sinha*, Stanford University; John Duchi, Optimal Tagging with Markov Chain Optimization

Nir Rosenfeld*, Hebrew University of Jerusalem; Amir Globerson, Tel Aviv University



Nir Rosenfeld*, Hebrew University of Jerusalem; Amir Globerson, Tel Aviv University Crowdsourced Clustering: Querying Edges vs Triangles

Ramya Korlakai Vinayak*, Caltech; Hassibi Babak, Caltech



Ramya Korlakai Vinayak*, Caltech; Hassibi Babak, Caltech Mixed vine copulas as joint models of spike counts and local field potentials

Arno Onken*, IIT; Stefano Panzeri, IIT



Arno Onken*, IIT; Stefano Panzeri, IIT Achieving the KS threshold in the general stochastic block model with linearized acyclic belief propagation

Emmanuel Abbe*, ; Colin Sandon,



Emmanuel Abbe*, ; Colin Sandon, Adaptive Concentration Inequalities for Sequential Decision Problems

Shengjia Zhao*, Tsinghua University; Enze Zhou, Tsinghua University; Ashish Sabharwal, Allen Institute for AI; Stefano Ermon,

Shengjia Zhao*, Tsinghua University; Enze Zhou, Tsinghua University; Ashish Sabharwal, Allen Institute for AI; Stefano Ermon, Fast mini-batch k-means by nesting

James Newling*, Idiap Research Institute; Francois Fleuret, Idiap Research Institute



James Newling*, Idiap Research Institute; Francois Fleuret, Idiap Research Institute Deep Learning Models of the Retinal Response to Natural Scenes

Lane McIntosh*, Stanford University; Niru Maheswaranathan, Stanford University; Aran Nayebi, Stanford University; Surya Ganguli, Stanford; Stephen Baccus, Stanford University



Lane McIntosh*, Stanford University; Niru Maheswaranathan, Stanford University; Aran Nayebi, Stanford University; Surya Ganguli, Stanford; Stephen Baccus, Stanford University Preference Completion from Partial Rankings

Suriya Gunasekar*, UT Austin; Sanmi Koyejo, UIUC; Joydeep Ghosh, UT Austin



Suriya Gunasekar*, UT Austin; Sanmi Koyejo, UIUC; Joydeep Ghosh, UT Austin Dynamic Network Surgery for Efficient DNNs

Yiwen Guo*, Intel Labs China; Anbang Yao, ; Yurong Chen,



Yiwen Guo*, Intel Labs China; Anbang Yao, ; Yurong Chen, Learning a Metric Embedding for Face Recognition using the Multibatch Method

Oren Tadmor, OrCam; Tal Rosenwein, Orcam; Shai Shalev-Shwartz, OrCam; Yonatan Wexler*, OrCam; Amnon Shashua, OrCam



Oren Tadmor, OrCam; Tal Rosenwein, Orcam; Shai Shalev-Shwartz, OrCam; Yonatan Wexler*, OrCam; Amnon Shashua, OrCam A Pseudo-Bayesian Algorithm for Robust PCA

Tae-Hyun Oh*, KAIST; David Wipf, ; Yasuyuki Matsushita, Osaka University; In So Kweon, KAIST



Tae-Hyun Oh*, KAIST; David Wipf, ; Yasuyuki Matsushita, Osaka University; In So Kweon, KAIST End-to-End Kernel Learning with Supervised Convolutional Kernel Networks

Julien Mairal*, Inria



Julien Mairal*, Inria Stochastic Variance Reduction Methods for Saddle-Point Problems

P. Balamurugan, ; Francis Bach*,



P. Balamurugan, ; Francis Bach*, Flexible Models for Microclustering with Applications to Entity Resolution

Brenda Betancourt, Duke University; Giacomo Zanella, The University of Warick; Jeffrey Miller, Duke University; Hanna Wallach, Microsoft Research; Abbas Zaidi, Duke University; Rebecca C. Steorts*, Duke University



Brenda Betancourt, Duke University; Giacomo Zanella, The University of Warick; Jeffrey Miller, Duke University; Hanna Wallach, Microsoft Research; Abbas Zaidi, Duke University; Rebecca C. Steorts*, Duke University Catching heuristics are optimal control policies

Boris Belousov*, TU Darmstadt; Gerhard Neumann, ; Constantin Rothkopf, ; Jan Peters,



Boris Belousov*, TU Darmstadt; Gerhard Neumann, ; Constantin Rothkopf, ; Jan Peters, Bayesian optimization under mixed constraints with a slack-variable augmented Lagrangian

Victor Picheny, Institut National de la Recherche Agronomique; Robert Gramacy*, ; Stefan Wild, Argonne National Lab; Sebastien Le Digabel, École Polytechnique de Montréal



Victor Picheny, Institut National de la Recherche Agronomique; Robert Gramacy*, ; Stefan Wild, Argonne National Lab; Sebastien Le Digabel, École Polytechnique de Montréal Adaptive Neural Compilation

Rudy Bunel*, Oxford University; Alban Desmaison, Oxford; M. Pawan Kumar, University of Oxford; Pushmeet Kohli, ; Philip Torr,



Rudy Bunel*, Oxford University; Alban Desmaison, Oxford; M. Pawan Kumar, University of Oxford; Pushmeet Kohli, ; Philip Torr, Synthesis of MCMC and Belief Propagation

Sung-Soo Ahn*, KAIST; Misha Chertkov, Los Alamos National Laboratory; Jinwoo Shin, KAIST



Sung-Soo Ahn*, KAIST; Misha Chertkov, Los Alamos National Laboratory; Jinwoo Shin, KAIST Learning Treewidth-Bounded Bayesian Networks with Thousands of Variables

Mauro Scanagatta*, Idsia; Giorgio Corani, Idsia; Cassio Polpo de Campos, Queen's University Belfast; Marco Zaffalon, IDSIA



Mauro Scanagatta*, Idsia; Giorgio Corani, Idsia; Cassio Polpo de Campos, Queen's University Belfast; Marco Zaffalon, IDSIA Unifying Count-Based Exploration and Intrinsic Motivation

Marc Bellemare*, Google DeepMind; Srinivasan Sriram, ; Georg Ostrovski, Google DeepMind; Tom Schaul, ; David Saxton, Google DeepMind; Remi Munos, Google DeepMind



Marc Bellemare*, Google DeepMind; Srinivasan Sriram, ; Georg Ostrovski, Google DeepMind; Tom Schaul, ; David Saxton, Google DeepMind; Remi Munos, Google DeepMind Large Margin Discriminant Dimensionality Reduction in Prediction Space

Mohammad Saberian*, Netflix; Jose Costa Pereira, UC San Diego; Nuno Nvasconcelos, UC San Diego



Mohammad Saberian*, Netflix; Jose Costa Pereira, UC San Diego; Nuno Nvasconcelos, UC San Diego Stochastic Structured Prediction under Bandit Feedback

Artem Sokolov, Heidelberg University; Julia Kreutzer, Heidelberg University; Stefan Riezler*, Heidelberg University



Artem Sokolov, Heidelberg University; Julia Kreutzer, Heidelberg University; Stefan Riezler*, Heidelberg University Simple and Efficient Weighted Minwise Hashing

Anshumali Shrivastava*, Rice University



Anshumali Shrivastava*, Rice University Truncated Variance Reduction: A Unified Approach to Bayesian Optimization and Level-Set Estimation

Ilija Bogunovic*, EPFL Lausanne; Jonathan Scarlett, ; Andreas Krause, ; Volkan Cevher,



Ilija Bogunovic*, EPFL Lausanne; Jonathan Scarlett, ; Andreas Krause, ; Volkan Cevher, Structured Sparse Regression via Greedy Hard Thresholding

Prateek Jain, Microsoft Research; Nikhil Rao*, ; Inderjit Dhillon,



Prateek Jain, Microsoft Research; Nikhil Rao*, ; Inderjit Dhillon, Understanding Probabilistic Sparse Gaussian Process Approximations

Matthias Bauer*, University of Cambridge; Mark van der Wilk, University of Cambridge; Carl Rasmussen, University of Cambridge



Matthias Bauer*, University of Cambridge; Mark van der Wilk, University of Cambridge; Carl Rasmussen, University of Cambridge SEBOOST - Boosting Stochastic Learning Using Subspace Optimization Techniques

Elad Richardson*, Technion; Rom Herskovitz, ; Boris Ginsburg, ; Michael Zibulevsky,



Elad Richardson*, Technion; Rom Herskovitz, ; Boris Ginsburg, ; Michael Zibulevsky, Long-Term Trajectory Planning Using Hierarchical Memory Networks

Stephan Zheng*, Caltech; Yisong Yue, ; Patrick Lucey, Stats



Stephan Zheng*, Caltech; Yisong Yue, ; Patrick Lucey, Stats Learning Tree Structured Potential Games

Vikas Garg*, MIT; Tommi Jaakkola,



Vikas Garg*, MIT; Tommi Jaakkola, Observational-Interventional Priors for Dose-Response Learning

Ricardo Silva*,



Ricardo Silva*, Learning from Rational Behavior: Predicting Solutions to Unknown Linear Programs

Shahin Jabbari*, University of Pennsylvania; Ryan Rogers, University of Pennsylvania; Aaron Roth, ; Steven Wu, University of Pennsylvania



Shahin Jabbari*, University of Pennsylvania; Ryan Rogers, University of Pennsylvania; Aaron Roth, ; Steven Wu, University of Pennsylvania Identification and Overidentification of Linear Structural Equation Models

Bryant Chen*, UCLA



Bryant Chen*, UCLA Adaptive Skills Adaptive Partitions (ASAP)

Daniel Mankowitz*, Technion; Timothy Mann, Google DeepMind; Shie Mannor, Technion



Daniel Mankowitz*, Technion; Timothy Mann, Google DeepMind; Shie Mannor, Technion Multiple-Play Bandits in the Position-Based Model

Paul Lagrée*, Université Paris Sud; Claire Vernade, Université Paris Saclay; Olivier Cappe,



Paul Lagrée*, Université Paris Sud; Claire Vernade, Université Paris Saclay; Olivier Cappe, Optimal Black-Box Reductions Between Optimization Objectives

Zeyuan Allen-Zhu*, Princeton University; Elad Hazan,



Zeyuan Allen-Zhu*, Princeton University; Elad Hazan, On Valid Optimal Assignment Kernels and Applications to Graph Classification

Nils Kriege*, TU Dortmund; Pierre-Louis Giscard, University of York; Richard Wilson, University of York



Nils Kriege*, TU Dortmund; Pierre-Louis Giscard, University of York; Richard Wilson, University of York Robustness of classifiers: from adversarial to random noise

Alhussein Fawzi, ; Seyed-Mohsen Moosavi-Dezfooli*, EPFL; Pascal Frossard, EPFL



Alhussein Fawzi, ; Seyed-Mohsen Moosavi-Dezfooli*, EPFL; Pascal Frossard, EPFL A Non-convex One-Pass Framework for Factorization Machines and Rank-One Matrix Sensing

Ming Lin*, ; Jieping Ye,



Ming Lin*, ; Jieping Ye, Exploiting the Structure: Stochastic Gradient Methods Using Raw Clusters

Zeyuan Allen-Zhu*, Princeton University; Yang Yuan, Cornell University; Karthik Sridharan, University of Pennsylvania



Zeyuan Allen-Zhu*, Princeton University; Yang Yuan, Cornell University; Karthik Sridharan, University of Pennsylvania Combinatorial Multi-Armed Bandit with General Reward Functions

Wei Chen*, ; Wei Hu, Princeton University; Fu Li, The University of Texas at Austin; Jian Li, Tsinghua University; Yu Liu, Tsinghua University; Pinyan Lu, Shanghai University of Finance and Economics



Wei Chen*, ; Wei Hu, Princeton University; Fu Li, The University of Texas at Austin; Jian Li, Tsinghua University; Yu Liu, Tsinghua University; Pinyan Lu, Shanghai University of Finance and Economics Boosting with Abstention

Corinna Cortes, ; Giulia DeSalvo*, ; Mehryar Mohri,



Corinna Cortes, ; Giulia DeSalvo*, ; Mehryar Mohri, Regret of Queueing Bandits

Subhashini Krishnasamy, The University of Texas at Austin; Rajat Sen, The University of Texas at Austin; Ramesh Johari, ; Sanjay Shakkottai*, The University of Texas at Aus



Subhashini Krishnasamy, The University of Texas at Austin; Rajat Sen, The University of Texas at Austin; Ramesh Johari, ; Sanjay Shakkottai*, The University of Texas at Aus Deep Learning Games

Dale Schuurmans*, ; Martin Zinkevich, Google



Dale Schuurmans*, ; Martin Zinkevich, Google Globally Optimal Training of Generalized Polynomial Neural Networks with Nonlinear Spectral Methods

Antoine Gautier*, Saarland University; Quynh Nguyen, Saarland University; Matthias Hein, Saarland University



Antoine Gautier*, Saarland University; Quynh Nguyen, Saarland University; Matthias Hein, Saarland University Learning Volumetric 3D Object Reconstruction from Single-View with Projective Transformations

Xinchen Yan*, University of Michigan; Jimei Yang, ; Ersin Yumer, Adobe Research; Yijie Guo, University of Michigan; Honglak Lee, University of Michigan



Xinchen Yan*, University of Michigan; Jimei Yang, ; Ersin Yumer, Adobe Research; Yijie Guo, University of Michigan; Honglak Lee, University of Michigan A Credit Assignment Compiler for Joint Prediction

Kai-Wei Chang*, ; He He, University of Maryland; Stephane Ross, Google; Hal III, ; John Langford,



Kai-Wei Chang*, ; He He, University of Maryland; Stephane Ross, Google; Hal III, ; John Langford, Accelerating Stochastic Composition Optimization

Mengdi Wang*, ; Ji Liu,



Mengdi Wang*, ; Ji Liu, Reward Augmented Maximum Likelihood for Neural Structured Prediction

Mohammad Norouzi*, ; Dale Schuurmans, ; Samy Bengio, ; zhifeng Chen, ; Navdeep Jaitly, ; Mike Schuster, ; Yonghui Wu,



Mohammad Norouzi*, ; Dale Schuurmans, ; Samy Bengio, ; zhifeng Chen, ; Navdeep Jaitly, ; Mike Schuster, ; Yonghui Wu, Consistent Kernel Mean Estimation for Functions of Random Variables

Adam Scibior*, University of Cambridge; Carl-Johann Simon-Gabriel, MPI Tuebingen; Iliya Tolstikhin, ; Bernhard Schoelkopf,



Adam Scibior*, University of Cambridge; Carl-Johann Simon-Gabriel, MPI Tuebingen; Iliya Tolstikhin, ; Bernhard Schoelkopf, Towards Unifying Hamiltonian Monte Carlo and Slice Sampling

Yizhe Zhang*, Duke university; Xiangyu Wang, Duke University; Changyou Chen, ; Ricardo Henao, ; Kai Fan, Duke university; Lawrence Carin,



Yizhe Zhang*, Duke university; Xiangyu Wang, Duke University; Changyou Chen, ; Ricardo Henao, ; Kai Fan, Duke university; Lawrence Carin, Scalable Adaptive Stochastic Optimization Using Random Projections

Gabriel Krummenacher*, ETH Zurich; Brian Mcwilliams, Disney Research; Yannic Kilcher, ETH Zurich; Joachim Buhmann, ETH Zurich; Nicolai Meinshausen,



Gabriel Krummenacher*, ETH Zurich; Brian Mcwilliams, Disney Research; Yannic Kilcher, ETH Zurich; Joachim Buhmann, ETH Zurich; Nicolai Meinshausen, Variational Inference in Mixed Probabilistic Submodular Models

Josip Djolonga, ETH Zurich; Sebastian Tschiatschek*, ETH Zurich; Andreas Krause,



Josip Djolonga, ETH Zurich; Sebastian Tschiatschek*, ETH Zurich; Andreas Krause, Correlated-PCA: Principal Components' Analysis when Data and Noise are Correlated

Namrata Vaswani*, ; Han Guo, Iowa State University



Namrata Vaswani*, ; Han Guo, Iowa State University The Multi-fidelity Multi-armed Bandit

Kirthevasan Kandasamy*, CMU; Gautam Dasarathy, Carnegie Mellon University; Barnabas Poczos, ; Jeff Schneider, CMU



Kirthevasan Kandasamy*, CMU; Gautam Dasarathy, Carnegie Mellon University; Barnabas Poczos, ; Jeff Schneider, CMU Anchor-Free Correlated Topic Modeling: Identifiability and Algorithm

Kejun Huang*, University of Minnesota; Xiao Fu, University of Minnesota; Nicholas Sidiropoulos, University of Minnesota



Kejun Huang*, University of Minnesota; Xiao Fu, University of Minnesota; Nicholas Sidiropoulos, University of Minnesota Bootstrap Model Aggregation for Distributed Statistical Learning

JUN HAN, Dartmouth College; Qiang Liu*,



JUN HAN, Dartmouth College; Qiang Liu*, A scalable end-to-end Gaussian process adapter for irregularly sampled time series classification

Steven Cheng-Xian Li*, UMass Amherst; Benjamin Marlin,



Steven Cheng-Xian Li*, UMass Amherst; Benjamin Marlin, A Bandit Framework for Strategic Regression

Yang Liu*, Harvard University; Yiling Chen,



Yang Liu*, Harvard University; Yiling Chen, Architectural Complexity Measures of Recurrent Neural Networks

Saizheng Zhang*, University of Montreal; Yuhuai Wu, University of Toronto; Tong Che, IHES; Zhouhan Lin, University of Montreal; Roland Memisevic, University of Montreal; Ruslan Salakhutdinov, University of Toronto; Yoshua Bengio, U. Montreal



Saizheng Zhang*, University of Montreal; Yuhuai Wu, University of Toronto; Tong Che, IHES; Zhouhan Lin, University of Montreal; Roland Memisevic, University of Montreal; Ruslan Salakhutdinov, University of Toronto; Yoshua Bengio, U. Montreal Statistical Inference for Cluster Trees

Jisu Kim*, Carnegie Mellon University; Yen-Chi Chen, Carnegie Mellon University; Sivaraman Balakrishnan, Carnegie Mellon University; Alessandro Rinaldo, Carnegie Mellon University; Larry Wasserman, Carnegie Mellon University



Jisu Kim*, Carnegie Mellon University; Yen-Chi Chen, Carnegie Mellon University; Sivaraman Balakrishnan, Carnegie Mellon University; Alessandro Rinaldo, Carnegie Mellon University; Larry Wasserman, Carnegie Mellon University Contextual-MDPs for PAC Reinforcement Learning with Rich Observations

Akshay Krishnamurthy*, ; Alekh Agarwal, Microsoft; John Langford,



Akshay Krishnamurthy*, ; Alekh Agarwal, Microsoft; John Langford, Improved Deep Metric Learning with Multi-class N-pair Loss Objective

Kihyuk Sohn*,



Kihyuk Sohn*, Only H is left: Near-tight Episodic PAC RL

Christoph Dann*, Carnegie Mellon University; Emma Brunskill, Carnegie Mellon University

Christoph Dann*, Carnegie Mellon University; Emma Brunskill, Carnegie Mellon University Unsupervised Learning of Spoken Language with Visual Context

David Harwath*, MIT CSAIL; Antonio Torralba, MIT CSAIL; James Glass, MIT CSAIL



David Harwath*, MIT CSAIL; Antonio Torralba, MIT CSAIL; James Glass, MIT CSAIL Low-Rank Regression with Tensor Responses

Guillaume Rabusseau*, Aix-Marseille University; Hachem Kadri,



Guillaume Rabusseau*, Aix-Marseille University; Hachem Kadri, PAC-Bayesian Theory Meets Bayesian Inference

Pascal Germain*, ; Francis Bach, ; Alexandre Lacoste, ; Simon Lacoste-Julien, INRIA



Pascal Germain*, ; Francis Bach, ; Alexandre Lacoste, ; Simon Lacoste-Julien, INRIA Data Poisoning Attacks on Factorization-Based Collaborative Filtering

Bo Li*, Vanderbilt University; Yining Wang, Carnegie Mellon University; Aarti Singh, Carnegie Mellon University; yevgeniy Vorobeychik, Vanderbilt University



Bo Li*, Vanderbilt University; Yining Wang, Carnegie Mellon University; Aarti Singh, Carnegie Mellon University; yevgeniy Vorobeychik, Vanderbilt University Learned Region Sparsity and Diversity Also Predicts Visual Attention

Zijun Wei*, Stony Brook; Hossein Adeli, ; Minh Hoai, ; Gregory Zelinsky, ; Dimitris Samaras,



Zijun Wei*, Stony Brook; Hossein Adeli, ; Minh Hoai, ; Gregory Zelinsky, ; Dimitris Samaras, End-to-End Goal-Driven Web Navigation

Rodrigo Frassetto Nogueira*, New York University; Kyunghyun Cho, University of Montreal



Rodrigo Frassetto Nogueira*, New York University; Kyunghyun Cho, University of Montreal Automated scalable segmentation of neurons from multispectral images

Uygar Sümbül*, Columbia University; Douglas Roossien, University of Michigan, Ann Arbor; Dawen Cai, University of Michigan, Ann Arbor; John Cunningham, Columbia University; Liam Paninski,



Uygar Sümbül*, Columbia University; Douglas Roossien, University of Michigan, Ann Arbor; Dawen Cai, University of Michigan, Ann Arbor; John Cunningham, Columbia University; Liam Paninski, Privacy Odometers and Filters: Pay-as-you-Go Composition

Ryan Rogers*, University of Pennsylvania; Salil Vadhan, Harvard University; Aaron Roth, ; Jonathan Robert Ullman,



Ryan Rogers*, University of Pennsylvania; Salil Vadhan, Harvard University; Aaron Roth, ; Jonathan Robert Ullman, Minimax Estimation of Maximal Mean Discrepancy with Radial Kernels

Iliya Tolstikhin*, ; Bharath Sriperumbudur, ; Bernhard Schoelkopf,



Iliya Tolstikhin*, ; Bharath Sriperumbudur, ; Bernhard Schoelkopf, Adaptive optimal training of animal behavior

Ji Hyun Bak*, Princeton University; Jung Yoon Choi, ; Ilana Witten, ; Jonathan Pillow,



Ji Hyun Bak*, Princeton University; Jung Yoon Choi, ; Ilana Witten, ; Jonathan Pillow, Hierarchical Object Representation for Open-Ended Object Category Learning and Recognition

Hamidreza Kasaei*, IEETA, University of Aveiro



Hamidreza Kasaei*, IEETA, University of Aveiro Relevant sparse codes with variational information bottleneck

Matthew Chalk*, IST Austria; Olivier Marre, Institut de la vision; Gašper Tkačik, Institute of Science and Technology Austria



Matthew Chalk*, IST Austria; Olivier Marre, Institut de la vision; Gašper Tkačik, Institute of Science and Technology Austria Combinatorial Energy Learning for Image Segmentation

Jeremy Maitin-Shepard*, Google; Viren Jain, Google; Michal Januszewski, Google; Peter Li, ; Pieter Abbeel,



Jeremy Maitin-Shepard*, Google; Viren Jain, Google; Michal Januszewski, Google; Peter Li, ; Pieter Abbeel, Orthogonal Random Features

Felix Xinnan Yu*, ; Ananda Theertha Suresh, ; Krzysztof Choromanski, ; Dan Holtmann-Rice, ; Sanjiv Kumar, Google



Felix Xinnan Yu*, ; Ananda Theertha Suresh, ; Krzysztof Choromanski, ; Dan Holtmann-Rice, ; Sanjiv Kumar, Google Fast Active Set Methods for Online Spike Inference from Calcium Imaging

Johannes Friedrich*, Columbia University; Liam Paninski,



Johannes Friedrich*, Columbia University; Liam Paninski, Diffusion-Convolutional Neural Networks

James Atwood*, UMass Amherst



James Atwood*, UMass Amherst Bayesian latent structure discovery from multi-neuron recordings

Scott Linderman*, ; Ryan Adams, ; Jonathan Pillow,



Scott Linderman*, ; Ryan Adams, ; Jonathan Pillow, A Probabilistic Programming Approach To Probabilistic Data Analysis

Feras Saad*, MIT; Vikash Mansinghka, MIT



Feras Saad*, MIT; Vikash Mansinghka, MIT A Non-parametric Learning Method for Confidently Estimating Patient's Clinical State and Dynamics

William Hoiles*, University of California, Los ; Mihaela Van Der Schaar,



William Hoiles*, University of California, Los ; Mihaela Van Der Schaar, Inference by Reparameterization in Neural Population Codes

RAJKUMAR VASUDEVA RAJU, Rice University; Xaq Pitkow*,



RAJKUMAR VASUDEVA RAJU, Rice University; Xaq Pitkow*, Tensor Switching Networks

Chuan-Yung Tsai*, ; Andrew Saxe, ; David Cox,



Chuan-Yung Tsai*, ; Andrew Saxe, ; David Cox, Stochastic Gradient Richardson-Romberg Markov Chain Monte Carlo

Alain Durmus, Telecom ParisTech; Umut Simsekli*, ; Eric Moulines, Ecole Polytechnique; Roland Badeau, Telecom ParisTech; Gaël Richard, Telecom ParisTech



Alain Durmus, Telecom ParisTech; Umut Simsekli*, ; Eric Moulines, Ecole Polytechnique; Roland Badeau, Telecom ParisTech; Gaël Richard, Telecom ParisTech Coordinate-wise Power Method

Qi Lei*, UT AUSTIN; Kai Zhong, UT AUSTIN; Inderjit Dhillon,



Qi Lei*, UT AUSTIN; Kai Zhong, UT AUSTIN; Inderjit Dhillon, Learning Influence Functions from Incomplete Observations

Xinran He*, USC; Ke Xu, USC; David Kempe, USC; Yan Liu,



Xinran He*, USC; Ke Xu, USC; David Kempe, USC; Yan Liu, Learning Structured Sparsity in Deep Neural Networks

Wei Wen*, University of Pittsburgh; Chunpeng Wu, University of Pittsburgh; Yandan Wang, University of Pittsburgh; Yiran Chen, University of Pittsburgh; Hai Li, University of Pittsburg



Wei Wen*, University of Pittsburgh; Chunpeng Wu, University of Pittsburgh; Yandan Wang, University of Pittsburgh; Yiran Chen, University of Pittsburgh; Hai Li, University of Pittsburg Sample Complexity of Automated Mechanism Design

Nina Balcan, ; Tuomas Sandholm, Carnegie Mellon University; Ellen Vitercik*, Carnegie Mellon University



Nina Balcan, ; Tuomas Sandholm, Carnegie Mellon University; Ellen Vitercik*, Carnegie Mellon University Short-Dot: Computing Large Linear Transforms Distributedly Using Coded Short Dot Products

SANGHAMITRA DUTTA*, Carnegie Mellon University; Viveck Cadambe, Pennsylvania State University; Pulkit Grover, Carnegie Mellon University



SANGHAMITRA DUTTA*, Carnegie Mellon University; Viveck Cadambe, Pennsylvania State University; Pulkit Grover, Carnegie Mellon University Brains on Beats

Umut Güçlü*, Radboud University; Jordy Thielen, Radboud University; Michael Hanke, Otto-von-Guericke University Magdeburg; Marcel Van Gerven, Radboud University



Umut Güçlü*, Radboud University; Jordy Thielen, Radboud University; Michael Hanke, Otto-von-Guericke University Magdeburg; Marcel Van Gerven, Radboud University Learning Transferrable Representations for Unsupervised Domain Adaptation

Ozan Sener*, Cornell University; Hyun Oh Song, Google Research; Ashutosh Saxena, Brain of Things; Silvio Savarese, Stanford University



Ozan Sener*, Cornell University; Hyun Oh Song, Google Research; Ashutosh Saxena, Brain of Things; Silvio Savarese, Stanford University Stochastic Multiple Choice Learning for Training Diverse Deep Ensembles

Stefan Lee*, Indiana University; Senthil Purushwalkam, Carnegie Mellon; Michael Cogswell, Virginia Tech; Viresh Ranjan, Virginia Tech; David Crandall, Indiana University; Dhruv Batra,



Stefan Lee*, Indiana University; Senthil Purushwalkam, Carnegie Mellon; Michael Cogswell, Virginia Tech; Viresh Ranjan, Virginia Tech; David Crandall, Indiana University; Dhruv Batra, Active Learning from Imperfect Labelers

Songbai Yan*, University of California, San Diego; Kamalika Chaudhuri, University of California, San Diego; Tara Javidi, University of California, San Diego



Songbai Yan*, University of California, San Diego; Kamalika Chaudhuri, University of California, San Diego; Tara Javidi, University of California, San Diego Learning to Communicate with Deep Multi-Agent Reinforcement Learning

Jakob Foerster*, University of Oxford; Yannis Assael, University of Oxford; Nando de Freitas, University of Oxford; Shimon Whiteson,



Jakob Foerster*, University of Oxford; Yannis Assael, University of Oxford; Nando de Freitas, University of Oxford; Shimon Whiteson, Value Iteration Networks

Aviv Tamar*, ; Sergey Levine, ; Pieter Abbeel, ; Yi Wu, UC Berkeley; Garrett Thomas, UC Berkeley



Aviv Tamar*, ; Sergey Levine, ; Pieter Abbeel, ; Yi Wu, UC Berkeley; Garrett Thomas, UC Berkeley Blind Regression: Nonparametric Regression for Latent Variable Models via Collaborative Filtering

Dogyoon Song*, MIT; Christina Lee, MIT; Yihua Li, MIT; Devavrat Shah,



Dogyoon Song*, MIT; Christina Lee, MIT; Yihua Li, MIT; Devavrat Shah, On the Recursive Teaching Dimension of VC Classes

Bo Tang*, University of Oxford; Xi Chen, Columbia University; Yu Cheng, U of Southern California



Bo Tang*, University of Oxford; Xi Chen, Columbia University; Yu Cheng, U of Southern California InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets

Xi Chen*, UC Berkeley; OpenAI; Yan Duan, UC Berkeley; Rein Houthooft, Ghent University - iMinds; UC Berkeley; OpenAI; John Schulman, OpenAI; Ilya Sutskever, ; Pieter Abbeel,



Xi Chen*, UC Berkeley; OpenAI; Yan Duan, UC Berkeley; Rein Houthooft, Ghent University - iMinds; UC Berkeley; OpenAI; John Schulman, OpenAI; Ilya Sutskever, ; Pieter Abbeel, Hardness of Online Sleeping Combinatorial Optimization Problems

Satyen Kale*, ; Chansoo Lee, ; David Pal,



Satyen Kale*, ; Chansoo Lee, ; David Pal, Mixed Linear Regression with Multiple Components

Kai Zhong*, UT AUSTIN; Prateek Jain, Microsoft Research; Inderjit Dhillon,



Kai Zhong*, UT AUSTIN; Prateek Jain, Microsoft Research; Inderjit Dhillon, Sequential Neural Models with Stochastic Layers

Marco Fraccaro*, DTU; Søren Sønderby, KU; Ulrich Paquet, ; Ole Winther, DTU



Marco Fraccaro*, DTU; Søren Sønderby, KU; Ulrich Paquet, ; Ole Winther, DTU Stochastic Gradient Methods for Distributionally Robust Optimization with f-divergences

Hongseok Namkoong*, Stanford University; John Duchi,



Hongseok Namkoong*, Stanford University; John Duchi, Minimizing Quadratic Functions in Constant Time

Kohei Hayashi*, AIST; Yuichi Yoshida, NII



Kohei Hayashi*, AIST; Yuichi Yoshida, NII Improved Techniques for Training GANs

Tim Salimans*, ; Ian Goodfellow, OpenAI; Wojciech Zaremba, OpenAI; Vicki Cheung, OpenAI; Alec Radford, OpenAI; Xi Chen, UC Berkeley; OpenAI



Tim Salimans*, ; Ian Goodfellow, OpenAI; Wojciech Zaremba, OpenAI; Vicki Cheung, OpenAI; Alec Radford, OpenAI; Xi Chen, UC Berkeley; OpenAI DeepMath - Deep Sequence Models for Premise Selection

Geoffrey Irving*, ; Christian Szegedy, ; Alexander Alemi, Google; Francois Chollet, ; Josef Urban, Czech Technical University in Prague



Geoffrey Irving*, ; Christian Szegedy, ; Alexander Alemi, Google; Francois Chollet, ; Josef Urban, Czech Technical University in Prague Learning Multiagent Communication with Backpropagation

Sainbayar Sukhbaatar, NYU; Arthur Szlam, ; Rob Fergus*, New York University

Sainbayar Sukhbaatar, NYU; Arthur Szlam, ; Rob Fergus*, New York University Toward Deeper Understanding of Neural Networks: The Power of Initialization and a Dual View on Expressivity

Amit Daniely*, ; Roy Frostig, Stanford University; Yoram Singer, Google



Amit Daniely*, ; Roy Frostig, Stanford University; Yoram Singer, Google Learning the Number of Neurons in Deep Networks

Jose Alvarez*, NICTA; Mathieu Salzmann, EPFL



Jose Alvarez*, NICTA; Mathieu Salzmann, EPFL Finding significant combinations of features in the presence of categorical covariates

Laetitia Papaxanthos*, ETH Zurich; Felipe Llinares, ETH Zurich; Dean Bodenham, ETH Zurich; Karsten Borgwardt,



Laetitia Papaxanthos*, ETH Zurich; Felipe Llinares, ETH Zurich; Dean Bodenham, ETH Zurich; Karsten Borgwardt, Examples are not Enough, Learn to Criticize! Model Criticism for Interpretable Machine Learning

Been Kim*, ; Rajiv Khanna, UT Austin; Sanmi Koyejo, UIUC



Been Kim*, ; Rajiv Khanna, UT Austin; Sanmi Koyejo, UIUC Optimistic Bandit Convex Optimization

Scott Yang*, New York University; Mehryar Mohri,



Scott Yang*, New York University; Mehryar Mohri, Safe Policy Improvement by Minimizing Robust Baseline Regret

Mohamad Ghavamzadeh*, ; Marek Petrik, ; Yinlam Chow, Stanford University



Mohamad Ghavamzadeh*, ; Marek Petrik, ; Yinlam Chow, Stanford University Graphons, mergeons, and so on!

Justin Eldridge*, The Ohio State University; Mikhail Belkin, ; Yusu Wang, The Ohio State University



Justin Eldridge*, The Ohio State University; Mikhail Belkin, ; Yusu Wang, The Ohio State University Hierarchical Clustering via Spreading Metrics

Aurko Roy*, Georgia Tech; Sebastian Pokutta, GeorgiaTech



Aurko Roy*, Georgia Tech; Sebastian Pokutta, GeorgiaTech Learning Bayesian networks with ancestral constraints

Eunice Yuh-Jie Chen*, UCLA; Yujia Shen, ; Arthur Choi, ; Adnan Darwiche,



Eunice Yuh-Jie Chen*, UCLA; Yujia Shen, ; Arthur Choi, ; Adnan Darwiche, Pruning Random Forests for Prediction on a Budget

Feng Nan*, Boston University; Joseph Wang, Boston University; Venkatesh Saligrama,



Feng Nan*, Boston University; Joseph Wang, Boston University; Venkatesh Saligrama, Clustering with Bregman Divergences: an Asymptotic Analysis

Chaoyue Liu*, The Ohio State University; Mikhail Belkin,



Chaoyue Liu*, The Ohio State University; Mikhail Belkin, Variational Autoencoder for Deep Learning of Images, Labels and Captions

Yunchen Pu*, Duke University; Zhe Gan, Duke; Ricardo Henao, ; Xin Yuan, Bell Labs; chunyuan Li, Duke; Andrew Stevens, Duke University; Lawrence Carin,



Yunchen Pu*, Duke University; Zhe Gan, Duke; Ricardo Henao, ; Xin Yuan, Bell Labs; chunyuan Li, Duke; Andrew Stevens, Duke University; Lawrence Carin, Encode, Review, and Decode: Reviewer Module for Caption Generation

Zhilin Yang*, Carnegie Mellon University; Ye Yuan, Carnegie Mellon University; Yuexin Wu, Carnegie Mellon University; William Cohen, Carnegie Mellon University; Ruslan Salakhutdinov, University of Toronto



Zhilin Yang*, Carnegie Mellon University; Ye Yuan, Carnegie Mellon University; Yuexin Wu, Carnegie Mellon University; William Cohen, Carnegie Mellon University; Ruslan Salakhutdinov, University of Toronto Variational Gradient Descent: A General Purpose Bayesian Inference Algorithm

Qiang Liu*, ; Dilin Wang, Dartmouth College



Qiang Liu*, ; Dilin Wang, Dartmouth College A Bio-inspired Redundant Sensing Architecture

Anh Tuan Nguyen*, University of Minnesota; Jian Xu, University of Minnesota; Zhi Yang, University of Minnesota



Anh Tuan Nguyen*, University of Minnesota; Jian Xu, University of Minnesota; Zhi Yang, University of Minnesota Contextual semibandits via supervised learning oracles

Akshay Krishnamurthy*, ; Alekh Agarwal, Microsoft; Miro Dudik,



Akshay Krishnamurthy*, ; Alekh Agarwal, Microsoft; Miro Dudik, Blind Attacks on Machine Learners

Alex Beatson*, Princeton University; Zhaoran Wang, Princeton University; Han Liu,



Alex Beatson*, Princeton University; Zhaoran Wang, Princeton University; Han Liu, Universal Correspondence Network

Christopher Choy*, Stanford University; Manmohan Chandraker, NEC Labs America; JunYoung Gwak, Stanford University; Silvio Savarese, Stanford University



Christopher Choy*, Stanford University; Manmohan Chandraker, NEC Labs America; JunYoung Gwak, Stanford University; Silvio Savarese, Stanford University Satisfying Real-world Goals with Dataset Constraints

Gabriel Goh*, UC Davis; Andy Cotter, ; Maya Gupta, ; Michael Friedlander, UC Davis



Gabriel Goh*, UC Davis; Andy Cotter, ; Maya Gupta, ; Michael Friedlander, UC Davis Deep Learning for Predicting Human Strategic Behavior

Jason Hartford*, University of British Columbia; Kevin Leyton-Brown, ; James Wright, University of British Columbia



Jason Hartford*, University of British Columbia; Kevin Leyton-Brown, ; James Wright, University of British Columbia Phased Exploration with Greedy Exploitation in Stochastic Combinatorial Partial Monitoring Games

Sougata Chaudhuri*, University of Michigan ; Ambuj Tewari, University of Michigan



Sougata Chaudhuri*, University of Michigan ; Ambuj Tewari, University of Michigan Eliciting and Aggregating Categorical Data

Yiling Chen, ; Rafael Frongillo, ; Chien-Ju Ho*,



Yiling Chen, ; Rafael Frongillo, ; Chien-Ju Ho*, Measuring the reliability of MCMC inference with Bidirectional Monte Carlo

Roger Grosse, ; Siddharth Ancha, University of Toronto; Daniel Roy*,



Roger Grosse, ; Siddharth Ancha, University of Toronto; Daniel Roy*, Breaking the Bandwidth Barrier: Geometrical Adaptive Entropy Estimation

Weihao Gao, UIUC; Sewoong Oh*, ; Pramod Viswanath, UIUC



Weihao Gao, UIUC; Sewoong Oh*, ; Pramod Viswanath, UIUC Selective inference for group-sparse linear models

Fan Yang, University of Chicago; Rina Foygel Barber*, ; Prateek Jain, Microsoft Research; John Lafferty,



Fan Yang, University of Chicago; Rina Foygel Barber*, ; Prateek Jain, Microsoft Research; John Lafferty, Graph Clustering: Block-models and model free results

Yali Wan*, University of Washington; Marina Meila, University of Washington



Yali Wan*, University of Washington; Marina Meila, University of Washington Maximizing Influence in an Ising Network: A Mean-Field Optimal Solution

Christopher Lynn*, University of Pennsylvania; Dan Lee , University of Pennsylvania



Christopher Lynn*, University of Pennsylvania; Dan Lee , University of Pennsylvania Hypothesis Testing in Unsupervised Domain Adaptation with Applications in Neuroscience

Hao Zhou, University of Wisconsin Madiso; Vamsi Ithapu*, University of Wisconsin Madison; Sathya Ravi, University of Wisconsin Madiso; Vikas Singh, UW Madison; Grace Wahba, University of Wisconsin Madison; Sterling Johnson, University of Wisconsin Madison



Hao Zhou, University of Wisconsin Madiso; Vamsi Ithapu*, University of Wisconsin Madison; Sathya Ravi, University of Wisconsin Madiso; Vikas Singh, UW Madison; Grace Wahba, University of Wisconsin Madison; Sterling Johnson, University of Wisconsin Madison Geometric Dirichlet Means Algorithm for Topic Inference

Mikhail Yurochkin*, University of Michigan; Long Nguyen,



Mikhail Yurochkin*, University of Michigan; Long Nguyen, Structured Prediction Theory Based on Factor Graph Complexity

Corinna Cortes, ; Vitaly Kuznetsov*, Courant Institute; Mehryar Mohri, ; Scott Yang, New York University



Corinna Cortes, ; Vitaly Kuznetsov*, Courant Institute; Mehryar Mohri, ; Scott Yang, New York University Improved Dropout for Shallow and Deep Learning

Zhe Li, The University of Iowa; Boqing Gong, University of Central Florida; Tianbao Yang*, University of Iowa



Zhe Li, The University of Iowa; Boqing Gong, University of Central Florida; Tianbao Yang*, University of Iowa Constraints Based Convex Belief Propagation

Yaniv Tenzer*, The Hebrew University; Alexander Schwing, ; Kevin Gimpel, ; Tamir Hazan,



Yaniv Tenzer*, The Hebrew University; Alexander Schwing, ; Kevin Gimpel, ; Tamir Hazan, Error Analysis of Generalized Nyström Kernel Regression

Hong Chen, University of Texas; Haifeng Xia, Huazhong Agricultural University; Heng Huang*, University of Texas Arlington



Hong Chen, University of Texas; Haifeng Xia, Huazhong Agricultural University; Heng Huang*, University of Texas Arlington A Probabilistic Framework for Deep Learning

Ankit Patel, Baylor College of Medicine; Rice University; Tan Nguyen*, Rice University; Richard Baraniuk,



Ankit Patel, Baylor College of Medicine; Rice University; Tan Nguyen*, Rice University; Richard Baraniuk, General Tensor Spectral Co-clustering for Higher-Order Data

Tao Wu*, Purdue University; Austin Benson, Stanford University; David Gleich,



Tao Wu*, Purdue University; Austin Benson, Stanford University; David Gleich, Cyclades: Conflict-free Asynchronous Machine Learning

Xinghao Pan*, UC Berkeley; Stephen Tu, UC Berkeley; Maximilian Lam, UC Berkeley; Dimitris Papailiopoulos, ; Ce Zhang, Stanford; Michael Jordan, ; Kannan Ramchandran, ; Christopher Re, ; Ben Recht,



Xinghao Pan*, UC Berkeley; Stephen Tu, UC Berkeley; Maximilian Lam, UC Berkeley; Dimitris Papailiopoulos, ; Ce Zhang, Stanford; Michael Jordan, ; Kannan Ramchandran, ; Christopher Re, ; Ben Recht, Single Pass PCA of Matrix Products

Shanshan Wu*, UT Austin; Srinadh Bhojanapalli, TTI Chicago; Sujay Sanghavi, ; Alexandros G. Dimakis,



Shanshan Wu*, UT Austin; Srinadh Bhojanapalli, TTI Chicago; Sujay Sanghavi, ; Alexandros G. Dimakis, Stochastic Variational Deep Kernel Learning

Andrew Wilson*, Carnegie Mellon University; Zhiting Hu, Carnegie Mellon University; Ruslan Salakhutdinov, University of Toronto; Eric Xing, Carnegie Mellon University



Andrew Wilson*, Carnegie Mellon University; Zhiting Hu, Carnegie Mellon University; Ruslan Salakhutdinov, University of Toronto; Eric Xing, Carnegie Mellon University Interaction Screening: Efficient and Sample-Optimal Learning of Ising Models

Marc Vuffray*, Los Alamos National Laboratory; Sidhant Misra, Los Alamos National Laboratory; Andrey Lokhov, Los Alamos National Laboratory; Misha Chertkov, Los Alamos National Laboratory



Marc Vuffray*, Los Alamos National Laboratory; Sidhant Misra, Los Alamos National Laboratory; Andrey Lokhov, Los Alamos National Laboratory; Misha Chertkov, Los Alamos National Laboratory Long-term Causal Effects via Behavioral Game Theory

Panos Toulis*, University of Chicago; David Parkes, Harvard University



Panos Toulis*, University of Chicago; David Parkes, Harvard University Measuring Neural Net Robustness with Constraints

Osbert Bastani*, Stanford University; Yani Ioannou, University of Cambridge; Leonidas Lampropoulos, University of Pennsylvania; Dimitrios Vytiniotis, Microsoft Research; Aditya Nori, Microsoft Research; Antonio Criminisi,



Osbert Bastani*, Stanford University; Yani Ioannou, University of Cambridge; Leonidas Lampropoulos, University of Pennsylvania; Dimitrios Vytiniotis, Microsoft Research; Aditya Nori, Microsoft Research; Antonio Criminisi, Reshaped Wirtinger Flow for Solving Quadratic Systems of Equations

Huishuai Zhang*, Syracuse University; Yingbin Liang, Syracuse University



Huishuai Zhang*, Syracuse University; Yingbin Liang, Syracuse University Nearly Isometric Embedding by Relaxation

James McQueen*, University of Washington; Marina Meila, University of Washington; Dominique Joncas, Google



James McQueen*, University of Washington; Marina Meila, University of Washington; Dominique Joncas, Google Probabilistic Inference with Generating Functions for Poisson Latent Variable Models

Kevin Winner*, UMass CICS; Daniel Sheldon,



Kevin Winner*, UMass CICS; Daniel Sheldon, Causal meets Submodular: Subset Selection with Directed Information

Yuxun Zhou*, UC Berkeley; Costas Spanos,



Yuxun Zhou*, UC Berkeley; Costas Spanos, Depth from a Single Image by Harmonizing Overcomplete Local Network Predictions

Ayan Chakrabarti*, ; Jingyu Shao, UCLA; Greg Shakhnarovich,



Ayan Chakrabarti*, ; Jingyu Shao, UCLA; Greg Shakhnarovich, Deep Neural Networks with Inexact Matching for Person Re-Identification

Arulkumar Subramaniam, IIT Madras; Moitreya Chatterjee*, IIT Madras; Anurag Mittal, IIT Madras



Arulkumar Subramaniam, IIT Madras; Moitreya Chatterjee*, IIT Madras; Anurag Mittal, IIT Madras Global Analysis of Expectation Maximization for Mixtures of Two Gaussians

Ji Xu, Columbia university; Daniel Hsu*, ; Arian Maleki, Columbia University



Ji Xu, Columbia university; Daniel Hsu*, ; Arian Maleki, Columbia University Estimating the class prior and posterior from noisy positives and unlabeled data

Shanatnu Jain*, Indiana University; Martha White, ; Predrag Radivojac,



Shanatnu Jain*, Indiana University; Martha White, ; Predrag Radivojac, Kronecker Determinantal Point Processes

Zelda Mariet*, MIT; Suvrit Sra, MIT



Zelda Mariet*, MIT; Suvrit Sra, MIT Finite Sample Prediction and Recovery Bounds for Ordinal Embedding

Lalit Jain*, University of Wisconsin-Madison; Kevin Jamieson, UC Berkeley; Robert Nowak, University of Wisconsin Madison



Lalit Jain*, University of Wisconsin-Madison; Kevin Jamieson, UC Berkeley; Robert Nowak, University of Wisconsin Madison Feature-distributed sparse regression: a screen-and-clean approach

Jiyan Yang*, Stanford University; Michael Mahoney, ; Michael Saunders, Stanford University; Yuekai Sun, University of Michigan



Jiyan Yang*, Stanford University; Michael Mahoney, ; Michael Saunders, Stanford University; Yuekai Sun, University of Michigan Learning Bound for Parameter Transfer Learning

Wataru Kumagai*, Kanagawa University



Wataru Kumagai*, Kanagawa University Learning under uncertainty: a comparison between R-W and Bayesian approach

He Huang*, LIBR; Martin Paulus, LIBR



He Huang*, LIBR; Martin Paulus, LIBR Bi-Objective Online Matching and Submodular Allocations

Hossein Esfandiari*, University of Maryland; Nitish Korula, Google Research; Vahab Mirrokni, Google



Hossein Esfandiari*, University of Maryland; Nitish Korula, Google Research; Vahab Mirrokni, Google Quantized Random Projections and Non-Linear Estimation of Cosine Similarity

Ping Li, ; Michael Mitzenmacher, Harvard University; Martin Slawski*,



Ping Li, ; Michael Mitzenmacher, Harvard University; Martin Slawski*, The non-convex Burer-Monteiro approach works on smooth semidefinite programs

Nicolas Boumal, ; Vlad Voroninski*, MIT; Afonso Bandeira,



Nicolas Boumal, ; Vlad Voroninski*, MIT; Afonso Bandeira, Dimensionality Reduction of Massive Sparse Datasets Using Coresets

Dan Feldman, ; Mikhail Volkov*, MIT; Daniela Rus, MIT



Dan Feldman, ; Mikhail Volkov*, MIT; Daniela Rus, MIT Using Social Dynamics to Make Individual Predictions: Variational Inference with Stochastic Kinetic Model

Zhen Xu*, SUNY at Buffalo; Wen Dong, ; Sargur Srihari,



Zhen Xu*, SUNY at Buffalo; Wen Dong, ; Sargur Srihari, Supervised learning through the lens of compression

Ofir David*, Technion - Israel institute of technology; Shay Moran, Technion - Israel institue of Technology; Amir Yehudayoff, Technion - Israel institue of Technology



Ofir David*, Technion - Israel institute of technology; Shay Moran, Technion - Israel institue of Technology; Amir Yehudayoff, Technion - Israel institue of Technology Generative Shape Models: Joint Text Recognition and Segmentation with Very Little Training Data

Xinghua Lou*, Vicarious FPC Inc; Ken Kansky, ; Wolfgang Lehrach, ; CC Laan, ; Bhaskara Marthi, ; D. Scott Phoenix, ; Dileep George,



Xinghua Lou*, Vicarious FPC Inc; Ken Kansky, ; Wolfgang Lehrach, ; CC Laan, ; Bhaskara Marthi, ; D. Scott Phoenix, ; Dileep George, Image Restoration Using Very Deep Convolutional Encoder-Decoder Networks with Symmetric Skip Connections

Xiao-Jiao Mao, Nanjing University; Chunhua Shen*, ; Yu-Bin Yang,



Xiao-Jiao Mao, Nanjing University; Chunhua Shen*, ; Yu-Bin Yang, Object based Scene Representations using Fisher Scores of Local Subspace Projections

Mandar Dixit*, UC San Diego; Nuno Vasconcelos,



Mandar Dixit*, UC San Diego; Nuno Vasconcelos, Active Learning with Oracle Epiphany

Tzu-Kuo Huang, Microsoft Research; Lihong Li, Microsoft Research; Ara Vartanian, University of Wisconsin-Madison; Saleema Amershi, Microsoft; Xiaojin Zhu*,



Tzu-Kuo Huang, Microsoft Research; Lihong Li, Microsoft Research; Ara Vartanian, University of Wisconsin-Madison; Saleema Amershi, Microsoft; Xiaojin Zhu*, Statistical Inference for Pairwise Graphical Models Using Score Matching

Ming Yu*, The University of Chicago; Mladen Kolar, ; Varun Gupta, University of Chicago



Ming Yu*, The University of Chicago; Mladen Kolar, ; Varun Gupta, University of Chicago Improved Error Bounds for Tree Representations of Metric Spaces

Samir Chowdhury*, The Ohio State University; Facundo Memoli, ; Zane Smith,



Samir Chowdhury*, The Ohio State University; Facundo Memoli, ; Zane Smith, Can Peripheral Representations Improve Clutter Metrics on Complex Scenes?

Arturo Deza*, UCSB; Miguel Eckstein, UCSB



Arturo Deza*, UCSB; Miguel Eckstein, UCSB On Multiplicative Integration with Recurrent Neural Networks

Yuhuai Wu*, University of Toronto; Saizheng Zhang, University of Montreal; ying Zhang, University of Montreal; Yoshua Bengio, U. Montreal; Ruslan Salakhutdinov, University of Toronto



Yuhuai Wu*, University of Toronto; Saizheng Zhang, University of Montreal; ying Zhang, University of Montreal; Yoshua Bengio, U. Montreal; Ruslan Salakhutdinov, University of Toronto Learning HMMs with Nonparametric Emissions via Spectral Decompositions of Continuous Matrices

Kirthevasan Kandasamy*, CMU; Maruan Al-Shedivat, CMU; Eric Xing, Carnegie Mellon University



Kirthevasan Kandasamy*, CMU; Maruan Al-Shedivat, CMU; Eric Xing, Carnegie Mellon University Regret Bounds for Non-decomposable Metrics with Missing Labels

Nagarajan Natarajan*, Microsoft Research Bangalore; Prateek Jain, Microsoft Research



Nagarajan Natarajan*, Microsoft Research Bangalore; Prateek Jain, Microsoft Research Robust k-means: a Theoretical Revisit

ALEXANDROS GEORGOGIANNIS*, TECHNICAL UNIVERSITY OF CRETE



ALEXANDROS GEORGOGIANNIS*, TECHNICAL UNIVERSITY OF CRETE Bayesian optimization for automated model selection

Gustavo Malkomes, Washington University; Charles Schaff, Washington University in St. Louis; Roman Garnett*,



Gustavo Malkomes, Washington University; Charles Schaff, Washington University in St. Louis; Roman Garnett*, A Probabilistic Model of Social Decision Making based on Reward Maximization

Koosha Khalvati*, University of Washington; Seongmin Park, Cognitive Neuroscience Center; Jean-Claude Dreher, Centre de Neurosciences Cognitives; Rajesh Rao, University of Washington



Koosha Khalvati*, University of Washington; Seongmin Park, Cognitive Neuroscience Center; Jean-Claude Dreher, Centre de Neurosciences Cognitives; Rajesh Rao, University of Washington Balancing Suspense and Surprise: Timely Decision Making with Endogenous Information Acquisition

Ahmed Alaa*, UCLA; Mihaela Van Der Schaar,



Ahmed Alaa*, UCLA; Mihaela Van Der Schaar, Fast and Flexible Monotonic Functions with Ensembles of Lattices

Mahdi Fard, ; Kevin Canini, ; Andy Cotter, ; Jan Pfeifer, Google; Maya Gupta*,



Mahdi Fard, ; Kevin Canini, ; Andy Cotter, ; Jan Pfeifer, Google; Maya Gupta*, Conditional Generative Moment-Matching Networks

Yong Ren, Tsinghua University; Jun Zhu*, ; Jialian Li, Tsinghua University; Yucen Luo,



Yong Ren, Tsinghua University; Jun Zhu*, ; Jialian Li, Tsinghua University; Yucen Luo, Stochastic Gradient MCMC with Stale Gradients

Changyou Chen*, ; Nan Ding, Google; chunyuan Li, Duke; Yizhe Zhang, Duke university; Lawrence Carin,



Changyou Chen*, ; Nan Ding, Google; chunyuan Li, Duke; Yizhe Zhang, Duke university; Lawrence Carin, Composing graphical models with neural networks for structured representations and fast inference

Matthew Johnson, ; David Duvenaud*, ; Alex Wiltschko, Harvard University and Twitter; Ryan Adams, ; Sandeep Datta, Harvard Medical School



Matthew Johnson, ; David Duvenaud*, ; Alex Wiltschko, Harvard University and Twitter; Ryan Adams, ; Sandeep Datta, Harvard Medical School Noise-Tolerant Life-Long Matrix Completion via Adaptive Sampling

Nina Balcan, ; Hongyang Zhang*, CMU



Nina Balcan, ; Hongyang Zhang*, CMU Combinatorial semi-bandit with known covariance

Rémy Degenne*, Université Paris Diderot; Vianney Perchet,



Rémy Degenne*, Université Paris Diderot; Vianney Perchet, Matrix Completion has No Spurious Local Minimum

Rong Ge, ; Jason Lee, UC Berkeley; Tengyu Ma*, Princeton University



Rong Ge, ; Jason Lee, UC Berkeley; Tengyu Ma*, Princeton University The Multiscale Laplacian Graph Kernel

Risi Kondor*, ; Horace Pan, UChicago



Risi Kondor*, ; Horace Pan, UChicago Adaptive Averaging in Accelerated Descent Dynamics

Walid Krichene*, UC Berkeley; Alexandre Bayen, UC Berkeley; Peter Bartlett,



Walid Krichene*, UC Berkeley; Alexandre Bayen, UC Berkeley; Peter Bartlett, Sub-sampled Newton Methods with Non-uniform Sampling

Peng Xu*, Stanford University; Jiyan Yang, Stanford University; Farbod Roosta-Khorasani, University of California Berkeley; Christopher Re, ; Michael Mahoney,



Peng Xu*, Stanford University; Jiyan Yang, Stanford University; Farbod Roosta-Khorasani, University of California Berkeley; Christopher Re, ; Michael Mahoney, Stochastic Gradient Geodesic MCMC Methods

Chang Liu*, Tsinghua University; Jun Zhu, ; Yang Song, Stanford University



Chang Liu*, Tsinghua University; Jun Zhu, ; Yang Song, Stanford University Variational Bayes on Monte Carlo Steroids

Aditya Grover*, Stanford University; Stefano Ermon,



Aditya Grover*, Stanford University; Stefano Ermon, Showing versus doing: Teaching by demonstration

Mark Ho*, Brown University; Michael L. Littman, ; James MacGlashan, Brown University; Fiery Cushman, Harvard University; Joe Austerweil,



Mark Ho*, Brown University; Michael L. Littman, ; James MacGlashan, Brown University; Fiery Cushman, Harvard University; Joe Austerweil, Combining Fully Convolutional and Recurrent Neural Networks for 3D Biomedical Image Segmentation

Jianxu Chen*, University of Notre Dame; Lin Yang, University of Notre Dame; Yizhe Zhang, University of Notre Dame; Mark Alber, University of Notre Dame; Danny Chen, University of Notre Dame



Jianxu Chen*, University of Notre Dame; Lin Yang, University of Notre Dame; Yizhe Zhang, University of Notre Dame; Mark Alber, University of Notre Dame; Danny Chen, University of Notre Dame Maximization of Approximately Submodular Functions

Thibaut Horel*, Harvard University; Yaron Singer,



Thibaut Horel*, Harvard University; Yaron Singer, A Comprehensive Linear Speedup Analysis for Asynchronous Stochastic Parallel Optimization from Zeroth-Order to First-Order

Xiangru Lian, University of Rochester; Huan Zhang, ; Cho-Jui Hsieh, ; Yijun Huang, ; Ji Liu*,



Xiangru Lian, University of Rochester; Huan Zhang, ; Cho-Jui Hsieh, ; Yijun Huang, ; Ji Liu*, Learning Infinite RBMs with Frank-Wolfe

Wei Ping*, UC Irvine; Qiang Liu, ; Alexander Ihler,



Wei Ping*, UC Irvine; Qiang Liu, ; Alexander Ihler, Estimating the Size of a Large Network and its Communities from a Random Sample

Lin Chen*, Yale University; Amin Karbasi, ; Forrest Crawford, Yale University



Lin Chen*, Yale University; Amin Karbasi, ; Forrest Crawford, Yale University Learning Sensor Multiplexing Design through Back-propagation

Ayan Chakrabarti*,



Ayan Chakrabarti*, On Robustness of Kernel Clustering

Bowei Yan*, University of Texas at Austin; Purnamrita Sarkar, U.C. Berkeley



Bowei Yan*, University of Texas at Austin; Purnamrita Sarkar, U.C. Berkeley High resolution neural connectivity from incomplete tracing data using nonnegative spline regression

Kameron Harris*, University of Washington; Stefan Mihalas, Allen Institute for Brain Science; Eric Shea-Brown, University of Washington



Kameron Harris*, University of Washington; Stefan Mihalas, Allen Institute for Brain Science; Eric Shea-Brown, University of Washington MoCap-guided Data Augmentation for 3D Pose Estimation in the Wild

Gregory Rogez*, Inria; Cordelia Schmid,



Gregory Rogez*, Inria; Cordelia Schmid, A New Liftable Class for First-Order Probabilistic Inference

Seyed Mehran Kazemi*, UBC; Angelika Kimmig, KU Leuven; Guy Van den Broeck, ; David Poole, UBC



Seyed Mehran Kazemi*, UBC; Angelika Kimmig, KU Leuven; Guy Van den Broeck, ; David Poole, UBC The Parallel Knowledge Gradient Method for Batch Bayesian Optimization

Jian Wu*, Cornell University; Peter I. Frazier,



Jian Wu*, Cornell University; Peter I. Frazier, Improved Regret Bounds for Oracle-Based Adversarial Contextual Bandits

Vasilis Syrgkanis*, ; Haipeng Luo, Princeton University; Akshay Krishnamurthy, ; Robert Schapire,



Vasilis Syrgkanis*, ; Haipeng Luo, Princeton University; Akshay Krishnamurthy, ; Robert Schapire, Consistent Estimation of Functions of Data Missing Non-Monotonically and Not at Random

Ilya Shpitser*,



Ilya Shpitser*, Optimistic Gittins Indices

Eli Gutin*, Massachusetts Institute of Tec; Vivek Farias,



Eli Gutin*, Massachusetts Institute of Tec; Vivek Farias, Finite-Dimensional BFRY Priors and Variational Bayesian Inference for Power Law Models

Juho Lee*, POSTECH; Lancelot James, HKUST; Seungjin Choi, POSTECH



Juho Lee*, POSTECH; Lancelot James, HKUST; Seungjin Choi, POSTECH Launch and Iterate: Reducing Prediction Churn

Mahdi Fard, ; Quentin Cormier, Google; Kevin Canini, ; Maya Gupta*,



Mahdi Fard, ; Quentin Cormier, Google; Kevin Canini, ; Maya Gupta*, “Congruent” and “Opposite” Neurons: Sisters for Multisensory Integration and Segregation

Wen-Hao Zhang*, Institute of Neuroscience, Chinese Academy of Sciences; He Wang, HKUST; K. Y. Michael Wong, HKUST; Si Wu,



Wen-Hao Zhang*, Institute of Neuroscience, Chinese Academy of Sciences; He Wang, HKUST; K. Y. Michael Wong, HKUST; Si Wu, Learning shape correspondence with anisotropic convolutional neural networks

Davide Boscaini*, University of Lugano; Jonathan Masci, ; Emanuele Rodolà, University of Lugano; Michael Bronstein, University of Lugano



Davide Boscaini*, University of Lugano; Jonathan Masci, ; Emanuele Rodolà, University of Lugano; Michael Bronstein, University of Lugano Pairwise Choice Markov Chains

Stephen Ragain*, Stanford University; Johan Ugander,



Stephen Ragain*, Stanford University; Johan Ugander, NESTT: A Nonconvex Primal-Dual Splitting Method for Distributed and Stochastic Optimization

Davood Hajinezhad*, Iowa State University; Mingyi Hong, ; Tuo Zhao, Johns Hopkins University; Zhaoran Wang, Princeton University



Davood Hajinezhad*, Iowa State University; Mingyi Hong, ; Tuo Zhao, Johns Hopkins University; Zhaoran Wang, Princeton University Clustering with Same-Cluster Queries

Hassan Ashtiani, University of Waterloo; Shrinu Kushagra*, University of Waterloo; Shai Ben-David, U. Waterloo



Hassan Ashtiani, University of Waterloo; Shrinu Kushagra*, University of Waterloo; Shai Ben-David, U. Waterloo Attend, Infer, Repeat: Fast Scene Understanding with Generative Models

S. M. Ali Eslami*, Google DeepMind; Nicolas Heess, ; Theophane Weber, ; Yuval Tassa, Google DeepMind; David Szepesvari, Google DeepMind; Koray Kavukcuoglu, Google DeepMind; Geoffrey Hinton, Google



S. M. Ali Eslami*, Google DeepMind; Nicolas Heess, ; Theophane Weber, ; Yuval Tassa, Google DeepMind; David Szepesvari, Google DeepMind; Koray Kavukcuoglu, Google DeepMind; Geoffrey Hinton, Google Parameter Learning for Log-supermodular Distributions

Tatiana Shpakova*, Inria - ENS Paris; Francis Bach,



Tatiana Shpakova*, Inria - ENS Paris; Francis Bach, Deconvolving Feedback Loops in Recommender Systems

Ayan Sinha*, Purdue; David Gleich, ; Karthik Ramani, Purdue University



Ayan Sinha*, Purdue; David Gleich, ; Karthik Ramani, Purdue University Structured Matrix Recovery via the Generalized Dantzig Selector

Sheng Chen*, University of Minnesota; Arindam Banerjee,



Sheng Chen*, University of Minnesota; Arindam Banerjee, Confusions over Time: An Interpretable Bayesian Model to Characterize Trends in Decision Making

Himabindu Lakkaraju*, Stanford University; Jure Leskovec,



Himabindu Lakkaraju*, Stanford University; Jure Leskovec, Automatic Neuron Detection in Calcium Imaging Data Using Convolutional Networks

Noah Apthorpe*, Princeton University; Alexander Riordan, Princeton University; Robert Aguilar, Princeton University; Jan Homann, Princeton University; Yi Gu, Princeton University; David Tank, Princeton University; H. Sebastian Seung, Princeton University



Noah Apthorpe*, Princeton University; Alexander Riordan, Princeton University; Robert Aguilar, Princeton University; Jan Homann, Princeton University; Yi Gu, Princeton University; David Tank, Princeton University; H. Sebastian Seung, Princeton University Designing smoothing functions for improved worst-case competitive ratio in online optimization

Reza Eghbali*, University of washington; Maryam Fazel, University of Washington



Reza Eghbali*, University of washington; Maryam Fazel, University of Washington Convergence guarantees for kernel-based quadrature rules in misspecified settings

Motonobu Kanagawa*, ; Bharath Sriperumbudur, ; Kenji Fukumizu,



Motonobu Kanagawa*, ; Bharath Sriperumbudur, ; Kenji Fukumizu, Unsupervised Learning from Noisy Networks with Applications to Hi-C Data

Bo Wang*, Stanford University; Junjie Zhu, Stanford University; Armin Pourshafeie, Stanford University



Bo Wang*, Stanford University; Junjie Zhu, Stanford University; Armin Pourshafeie, Stanford University A non-generative framework and convex relaxations for unsupervised learning

Elad Hazan, ; Tengyu Ma*, Princeton University



Elad Hazan, ; Tengyu Ma*, Princeton University Equality of Opportunity in Supervised Learning

Moritz Hardt*, ; Eric Price, ; Nathan Srebro,



Moritz Hardt*, ; Eric Price, ; Nathan Srebro, Scaled Least Squares Estimator for GLMs in Large-Scale Problems

Murat Erdogdu*, Stanford University; Lee Dicker, ; Mohsen Bayati,



Murat Erdogdu*, Stanford University; Lee Dicker, ; Mohsen Bayati, Interpretable Nonlinear Dynamic Modeling of Neural Trajectories

Yuan Zhao*, Stony Brook University; Il Memming Park,



Yuan Zhao*, Stony Brook University; Il Memming Park, Search Improves Label for Active Learning

Alina Beygelzimer, Yahoo Inc; Daniel Hsu, ; John Langford, ; Chicheng Zhang*, UCSD



Alina Beygelzimer, Yahoo Inc; Daniel Hsu, ; John Langford, ; Chicheng Zhang*, UCSD Higher-Order Factorization Machines

Mathieu Blondel*, NTT; Akinori Fujino, NTT; Naonori Ueda, ; Masakazu Ishihata, Hokkaido University



Mathieu Blondel*, NTT; Akinori Fujino, NTT; Naonori Ueda, ; Masakazu Ishihata, Hokkaido University Exponential expressivity in deep neural networks through transient chaos

Ben Poole*, Stanford University; Subhaneil Lahiri, Stanford University; Maithra Raghu, Cornell University; Jascha Sohl-Dickstein, ; Surya Ganguli, Stanford



Ben Poole*, Stanford University; Subhaneil Lahiri, Stanford University; Maithra Raghu, Cornell University; Jascha Sohl-Dickstein, ; Surya Ganguli, Stanford Split LBI: An Iterative Regularization Path with Structural Sparsity

Chendi Huang, Peking University; Xinwei Sun, ; Jiechao Xiong, Peking University; Yuan Yao*,



Chendi Huang, Peking University; Xinwei Sun, ; Jiechao Xiong, Peking University; Yuan Yao*, An equivalence between high dimensional Bayes optimal inference and M-estimation

Madhu Advani*, Stanford University; Surya Ganguli, Stanford



Madhu Advani*, Stanford University; Surya Ganguli, Stanford Synthesizing the preferred inputs for neurons in neural networks via deep generator networks

Anh Nguyen*, University of Wyoming; Alexey Dosovitskiy, ; Jason Yosinski, Cornell; Thomas Brox, University of Freiburg; Jeff Clune,



Anh Nguyen*, University of Wyoming; Alexey Dosovitskiy, ; Jason Yosinski, Cornell; Thomas Brox, University of Freiburg; Jeff Clune, Deep Submodular Functions

Brian Dolhansky*, University of Washington; Jeff Bilmes, University of Washington, Seattle



Brian Dolhansky*, University of Washington; Jeff Bilmes, University of Washington, Seattle Discriminative Gaifman Models

Mathias Niepert*,



Mathias Niepert*, Leveraging Sparsity for Efficient Submodular Data Summarization

Erik Lindgren*, University of Texas at Austin; Shanshan Wu, UT Austin; Alexandros G. Dimakis,



Erik Lindgren*, University of Texas at Austin; Shanshan Wu, UT Austin; Alexandros G. Dimakis, Local Minimax Complexity of Stochastic Convex Optimization

Sabyasachi Chatterjee, University of Chicago; John Duchi, ; John Lafferty, ; Yuancheng Zhu*, University of Chicago



Sabyasachi Chatterjee, University of Chicago; John Duchi, ; John Lafferty, ; Yuancheng Zhu*, University of Chicago Stochastic Optimization for Large-scale Optimal Transport

Aude Genevay*, Université Paris Dauphine; Marco Cuturi, ; Gabriel Peyré, ; Francis Bach,



Aude Genevay*, Université Paris Dauphine; Marco Cuturi, ; Gabriel Peyré, ; Francis Bach, On Mixtures of Markov Chains

Rishi Gupta*, Stanford; Ravi Kumar, ; Sergei Vassilvitskii, Google



Rishi Gupta*, Stanford; Ravi Kumar, ; Sergei Vassilvitskii, Google Linear Contextual Bandits with Knapsacks

Shipra Agrawal*, ; Nikhil Devanur, Microsoft Research



Shipra Agrawal*, ; Nikhil Devanur, Microsoft Research Reconstructing Parameters of Spreading Models from Partial Observations

Andrey Lokhov*, Los Alamos National Laboratory



Andrey Lokhov*, Los Alamos National Laboratory Spatiotemporal Residual Networksfor Video Action Recognition

Christoph Feichtenhofer*, Graz University of Technology; Axel Pinz, Graz University of Technology; Richard Wildes, York University Toronto



Christoph Feichtenhofer*, Graz University of Technology; Axel Pinz, Graz University of Technology; Richard Wildes, York University Toronto Path-Normalized Optimization of Recurrent Neural Networks with ReLU Activations

Behnam Neyshabur*, TTI-Chicago; Yuhuai Wu, University of Toronto; Ruslan Salakhutdinov, University of Toronto; Nathan Srebro,



Behnam Neyshabur*, TTI-Chicago; Yuhuai Wu, University of Toronto; Ruslan Salakhutdinov, University of Toronto; Nathan Srebro, Strategic Attentive Writer for Learning Macro-Actions

Alexander Vezhnevets*, Google DeepMind; Volodymyr Mnih, ; Simon Osindero, Google DeepMind; Alex Graves, ; Oriol Vinyals, ; John Agapiou, ; Koray Kavukcuoglu, Google DeepMind



Alexander Vezhnevets*, Google DeepMind; Volodymyr Mnih, ; Simon Osindero, Google DeepMind; Alex Graves, ; Oriol Vinyals, ; John Agapiou, ; Koray Kavukcuoglu, Google DeepMind The Limits of Learning with Missing Data

Brian Bullins*, Princeton University; Elad Hazan, ; Tomer Koren, Technion---Israel Inst. of Technology



Brian Bullins*, Princeton University; Elad Hazan, ; Tomer Koren, Technion---Israel Inst. of Technology RETAIN: Interpretable Predictive Model in Healthcare using Reverse Time Attention Mechanism

Edward Choi*, Georgia Institute of Technolog; Mohammad Taha Bahadori, Gatech; Jimeng Sun,



Edward Choi*, Georgia Institute of Technolog; Mohammad Taha Bahadori, Gatech; Jimeng Sun, Total Variation Classes Beyond 1d: Minimax Rates, and the Limitations of Linear Smoothers

Yu-Xiang Wang*, Carnegie Mellon University; Veeranjaneyulu Sadhanala, Carnegie Mellon University; Ryan Tibshirani,



Yu-Xiang Wang*, Carnegie Mellon University; Veeranjaneyulu Sadhanala, Carnegie Mellon University; Ryan