NeurIPS 2017

679 papers

Best Response Regression

Omer Ben-Porat, Moshe Tennenholtz

Convolutional Gaussian Processes

Mark van der Wilk, Carl Edward Rasmussen, James Hensman

Training Quantized Nets: A Deeper Understanding

Hao Li, Soham De, Zheng Xu, Christoph Studer, Hanan Samet

EX2: Exploration with Exemplar Models for Deep Reinforcement Learning

Justin Fu, John Co-Reyes, Sergey Levine

On Tensor Train Rank Minimization : Statistical Efficiency and Scalable Algorithm

Masaaki Imaizumi, Takanori Maehara, Kohei Hayashi

How regularization affects the critical points in linear networks

Amirhossein Taghvaei, Jin W Kim, Prashant Mehta

Variational Laws of Visual Attention for Dynamic Scenes

Dario Zanca, Marco Gori

YASS: Yet Another Spike Sorter

Jin Hyung Lee, David E Carlson, Hooshmand Shokri Razaghi, Weichi Yao, Georges A Goetz

Differentiable Learning of Submodular Models

Josip Djolonga, Andreas Krause

Premise Selection for Theorem Proving by Deep Graph Embedding

Mingzhe Wang, Yihe Tang, Jian Wang, Jia Deng

Polynomial time algorithms for dual volume sampling

Chengtao Li, Stefanie Jegelka, Suvrit Sra

Collaborative PAC Learning

Avrim Blum, Nika Haghtalab, Ariel D Procaccia, Mingda Qiao

Expectation Propagation for t-Exponential Family Using q-Algebra

Futoshi Futami, Issei Sato, Masashi Sugiyama

Stein Variational Gradient Descent as Gradient Flow

Qiang Liu

Unifying PAC and Regret: Uniform PAC Bounds for Episodic Reinforcement Learning

Christoph Dann, Tor Lattimore, Emma Brunskill

Phase Transitions in the Pooled Data Problem

Jonathan Scarlett, Volkan Cevher

Semi-Supervised Learning for Optical Flow with Generative Adversarial Networks

Wei-Sheng Lai, Jia-Bin Huang, Ming-Hsuan Yang

Efficient Modeling of Latent Information in Supervised Learning using Gaussian Processes

Zhenwen Dai, Mauricio Alvarez, Neil Lawrence

Learning Linear Dynamical Systems via Spectral Filtering

Elad Hazan, Karan Singh, Cyril Zhang

Aggressive Sampling for Multi-class to Binary Reduction with Applications to Text Classification

Bikash Joshi, Massih R. Amini, Ioannis Partalas, Franck Iutzeler, Yury Maximov

Neural Variational Inference and Learning in Undirected Graphical Models

Volodymyr Kuleshov, Stefano Ermon

Learning to Model the Tail

Yu-Xiong Wang, Deva Ramanan, Martial Hebert

k-Support and Ordered Weighted Sparsity for Overlapping Groups: Hardness and Algorithms

Cong Han Lim, Stephen Wright

Diffusion Approximations for Online Principal Component Estimation and Global Convergence

Chris Junchi Li, Mengdi Wang, Han Liu, Tong Zhang

A Universal Analysis of Large-Scale Regularized Least Squares Solutions

Ashkan Panahi, Babak Hassibi

Dualing GANs

Yujia Li, Alexander Schwing, Kuan-Chieh Wang, Richard Zemel

When Worlds Collide: Integrating Different Counterfactual Assumptions in Fairness

Chris Russell, Matt J Kusner, Joshua Loftus, Ricardo Silva

Hybrid Reward Architecture for Reinforcement Learning

Harm Van Seijen, Mehdi Fatemi, Joshua Romoff, Romain Laroche, Tavian Barnes

Introspective Classification with Convolutional Nets

Long Jin, Justin Lazarow, Zhuowen Tu

Safe Adaptive Importance Sampling

Sebastian U Stich, Anant Raj, Martin Jaggi

Spherical convolutions and their application in molecular modelling

Wouter Boomsma, Jes Frellsen

Exploring Generalization in Deep Learning

Behnam Neyshabur, Srinadh Bhojanapalli, David Mcallester, Nati Srebro

Robust Optimization for Non-Convex Objectives

Robert S. Chen, Brendan Lucier, Yaron Singer, Vasilis Syrgkanis

Estimation of the covariance structure of heavy-tailed distributions

Xiaohan Wei, Stanislav Minsker

Identification of Gaussian Process State Space Models

Stefanos Eleftheriadis, Tom Nicholson, Marc Deisenroth, James Hensman

Nonlinear random matrix theory for deep learning

Jeffrey Pennington, Pratik Worah

Continual Learning with Deep Generative Replay

Hanul Shin, Jung Kwon Lee, Jaehong Kim, Jiwon Kim

Principles of Riemannian Geometry in Neural Networks

Michael Hauser, Asok Ray

When Cyclic Coordinate Descent Outperforms Randomized Coordinate Descent

Mert Gurbuzbalaban, Asuman Ozdaglar, Pablo A Parrilo, Nuri Vanli

Differentiable Learning of Logical Rules for Knowledge Base Reasoning

Fan Yang, Zhilin Yang, William W. Cohen

Approximate Supermodularity Bounds for Experimental Design

Luiz Chamon, Alejandro Ribeiro

Learning Spherical Convolution for Fast Features from 360° Imagery

Yu-Chuan Su, Kristen Grauman

Real-Time Bidding with Side Information

arthur flajolet, Patrick Jaillet

Distral: Robust multitask reinforcement learning

Yee Teh, Victor Bapst, Wojciech M. Czarnecki, John Quan, James Kirkpatrick

Recurrent Ladder Networks

Isabeau Prémont-Schwarz, Alexander Ilin, Tele Hao, Antti Rasmus, Rinu Boney

Unsupervised Learning of Disentangled and Interpretable Representations from Sequential Data

Wei-Ning Hsu, Yu Zhang, James Glass

Adaptive SVRG Methods under Error Bound Conditions with Unknown Growth Parameter

Yi Xu, Qihang Lin, Tianbao Yang

State Aware Imitation Learning

Yannick Schroecker, Charles L Isbell

Online multiclass boosting

Young Hun Jung, Jack Goetz, Ambuj Tewari

PASS-GLM: polynomial approximate sufficient statistics for scalable Bayesian GLM inference

Jonathan Huggins, Ryan P. Adams, Tamara Broderick

Best of Both Worlds: Transferring Knowledge from Discriminative Learning to a Generative Visual Dialog Model

Jiasen Lu, Anitha Kannan, Jianwei Yang, Devi Parikh, Dhruv Batra

Deep Hyperalignment

Muhammad Yousefnezhad, Daoqiang Zhang

A Bayesian Data Augmentation Approach for Learning Deep Models

Toan Tran, Trung Pham, Gustavo Carneiro, Lyle Palmer, Ian Reid

A New Theory for Matrix Completion

Guangcan Liu, Qingshan Liu, Xiaotong Yuan

Breaking the Nonsmooth Barrier: A Scalable Parallel Method for Composite Optimization

Fabian Pedregosa, Rémi Leblond, Simon Lacoste-Julien

Kernel functions based on triplet comparisons

Matthäus Kleindessner, Ulrike Von Luxburg

Minimax Estimation of Bandable Precision Matrices

Addison Hu, Sahand Negahban

Fisher GAN

Youssef Mroueh, Tom Sercu

Generalized Linear Model Regression under Distance-to-set Penalties

Jason Xu, Eric Chi, Kenneth Lange

FALKON: An Optimal Large Scale Kernel Method

Alessandro Rudi, Luigi Carratino, Lorenzo Rosasco

High-Order Attention Models for Visual Question Answering

Idan Schwartz, Alexander Schwing, Tamir Hazan

Robust Imitation of Diverse Behaviors

Ziyu Wang, Josh S Merel, Scott E Reed, Nando de Freitas, Gregory Wayne

Non-parametric Structured Output Networks

Andreas Lehrmann, Leonid Sigal

Query Complexity of Clustering with Side Information

Arya Mazumdar, Barna Saha

Learning Multiple Tasks with Multilinear Relationship Networks

Mingsheng Long, ZHANGJIE CAO, Jianmin Wang, Philip S Yu

Model-Powered Conditional Independence Test

Rajat Sen, Ananda Theertha Suresh, Karthikeyan Shanmugam, Alexandros G Dimakis, Sanjay Shakkottai

Scalable Levy Process Priors for Spectral Kernel Learning

Phillip A Jang, Andrew Loeb, Matthew Davidow, Andrew G Wilson

Adaptive Bayesian Sampling with Monte Carlo EM

Anirban Roychowdhury, Srinivasan Parthasarathy

Saliency-based Sequential Image Attention with Multiset Prediction

Sean Welleck, Jialin Mao, Kyunghyun Cho, Zheng Zhang

Accelerated consensus via Min-Sum Splitting

Patrick Rebeschini, Sekhar C Tatikonda

Few-Shot Learning Through an Information Retrieval Lens

Eleni Triantafillou, Richard Zemel, Raquel Urtasun

Beyond Worst-case: A Probabilistic Analysis of Affine Policies in Dynamic Optimization

Omar El Housni, Vineet Goyal

Langevin Dynamics with Continuous Tempering for Training Deep Neural Networks

Nanyang Ye, Zhanxing Zhu, Rafal Mantiuk

On clustering network-valued data

Soumendu Sundar Mukherjee, Purnamrita Sarkar, Lizhen Lin

Inverse Filtering for Hidden Markov Models

Robert Mattila, Cristian Rojas, Vikram Krishnamurthy, Bo Wahlberg

Learning to Inpaint for Image Compression

Mohammad Haris Baig, Vladlen Koltun, Lorenzo Torresani

Learning A Structured Optimal Bipartite Graph for Co-Clustering

Feiping Nie, Xiaoqian Wang, Cheng Deng, Heng Huang

Joint distribution optimal transportation for domain adaptation

Nicolas Courty, Rémi Flamary, Amaury Habrard, Alain Rakotomamonjy

Real Time Image Saliency for Black Box Classifiers

Piotr Dabkowski, Yarin Gal