NeurIPS 2019

1,428 papers

Unsupervised State Representation Learning in Atari

Ankesh Anand, Evan Racah, Sherjil Ozair, Yoshua Bengio, Marc-Alexandre Côté

Learning from Trajectories via Subgoal Discovery

Sujoy Paul, Jeroen Vanbaar, Amit Roy-Chowdhury

Image Synthesis with a Single (Robust) Classifier

Shibani Santurkar, Andrew Ilyas, Dimitris Tsipras, Logan Engstrom, Brandon Tran

Learning search spaces for Bayesian optimization: Another view of hyperparameter transfer learning

Valerio Perrone, Huibin Shen, Matthias W Seeger, Cédric Archambeau, Rodolphe Jenatton

Memory-oriented Decoder for Light Field Salient Object Detection

Miao Zhang, Jingjing Li, JI WEI, Yongri Piao, Huchuan Lu

Functional Adversarial Attacks

Cassidy Laidlaw, Soheil Feizi

A unified theory for the origin of grid cells through the lens of pattern formation

Ben Sorscher, Gabriel Mel, Surya Ganguli, Samuel Ocko

Deep Set Prediction Networks

Yan Zhang, Jonathon Hare, Adam Prugel-Bennett

Riemannian batch normalization for SPD neural networks

Daniel Brooks, Olivier Schwander, Frederic Barbaresco, Jean-Yves Schneider, Matthieu Cord

Scalable Gromov-Wasserstein Learning for Graph Partitioning and Matching

Hongteng Xu, Dixin Luo, Lawrence Carin

Algorithm-Dependent Generalization Bounds for Overparameterized Deep Residual Networks

Spencer Frei, Yuan Cao, Quanquan Gu

Novel positional encodings to enable tree-based transformers

Vighnesh Shiv, Chris Quirk

Category Anchor-Guided Unsupervised Domain Adaptation for Semantic Segmentation

Qiming ZHANG, Jing Zhang, Wei Liu, Dacheng Tao

Gradient Information for Representation and Modeling

Jie Ding, Robert Calderbank, Vahid Tarokh

Beyond Vector Spaces: Compact Data Representation as Differentiable Weighted Graphs

Denis Mazur, Vage Egiazarian, Stanislav Morozov, Artem Babenko

Online Optimal Control with Linear Dynamics and Predictions: Algorithms and Regret Analysis

Yingying Li, Xin Chen, Na Li

Efficient Probabilistic Inference in the Quest for Physics Beyond the Standard Model

Atilim Gunes Baydin, Lei Shao, Wahid Bhimji, Lukas Heinrich, Saeid Naderiparizi

Positional Normalization

Boyi Li, Felix Wu, Kilian Q. Weinberger, Serge Belongie

Scalable Global Optimization via Local Bayesian Optimization

David Eriksson, Michael Pearce, Jacob Gardner, Ryan D Turner, Matthias Poloczek

End-to-End Learning on 3D Protein Structure for Interface Prediction

Raphael Townshend, Rishi Bedi, Patricia Suriana, Ron Dror

Poincaré Recurrence, Cycles and Spurious Equilibria in Gradient-Descent-Ascent for Non-Convex Non-Concave Zero-Sum Games

Emmanouil-Vasileios Vlatakis-Gkaragkounis, Lampros Flokas, Georgios Piliouras

Effective End-to-end Unsupervised Outlier Detection via Inlier Priority of Discriminative Network

Siqi Wang, Yijie Zeng, Xinwang Liu, En Zhu, Jianping Yin

Efficient Forward Architecture Search

Hanzhang Hu, John Langford, Rich Caruana, Saurajit Mukherjee, Eric J Horvitz

Variance Reduction for Matrix Games

Yair Carmon, Yujia Jin, Aaron Sidford, Kevin Tian

On The Classification-Distortion-Perception Tradeoff

Dong Liu, Haochen Zhang, Zhiwei Xiong

A Solvable High-Dimensional Model of GAN

Chuang Wang, Hong Hu, Yue Lu

A state-space model for inferring effective connectivity of latent neural dynamics from simultaneous EEG/fMRI

Tao Tu, John Paisley, Stefan Haufe, Paul Sajda

Fast AutoAugment

Sungbin Lim, Ildoo Kim, Taesup Kim, Chiheon Kim, Sungwoong Kim

Contextual Bandits with Cross-Learning

Santiago Balseiro, Negin Golrezaei, Mohammad Mahdian, Vahab Mirrokni, Jon Schneider

Stochastic Proximal Langevin Algorithm: Potential Splitting and Nonasymptotic Rates

Adil SALIM, Dmitry Kovalev, Peter Richtarik

An Improved Analysis of Training Over-parameterized Deep Neural Networks

Difan Zou, Quanquan Gu

DM2C: Deep Mixed-Modal Clustering

Yangbangyan Jiang, Qianqian Xu, Zhiyong Yang, Xiaochun Cao, Qingming Huang

Selecting the independent coordinates of manifolds with large aspect ratios

Yu-Chia Chen, Marina Meila

Extreme Classification in Log Memory using Count-Min Sketch: A Case Study of Amazon Search with 50M Products

Tharun Kumar Reddy Medini, Qixuan Huang, Yiqiu Wang, Vijai Mohan, Anshumali Shrivastava

Grid Saliency for Context Explanations of Semantic Segmentation

Lukas Hoyer, Mauricio Munoz, Prateek Katiyar, Anna Khoreva, Volker Fischer

Enabling hyperparameter optimization in sequential autoencoders for spiking neural data

Mohammad Reza Keshtkaran, Chethan Pandarinath

A Domain Agnostic Measure for Monitoring and Evaluating GANs

Paulina Grnarova, Kfir Y. Levy, Aurelien Lucchi, Nathanael Perraudin, Ian Goodfellow

Differentially Private Algorithms for Learning Mixtures of Separated Gaussians

Gautam Kamath, Or Sheffet, Vikrant Singhal, Jonathan Ullman

Rethinking Generative Mode Coverage: A Pointwise Guaranteed Approach

Peilin Zhong, Yuchen Mo, Chang Xiao, Pengyu Chen, Changxi Zheng

Channel Gating Neural Networks

Weizhe Hua, Yuan Zhou, Christopher M De Sa, Zhiru Zhang, G. Edward Suh

Structured Variational Inference in Continuous Cox Process Models

Virginia Aglietti, Edwin V. Bonilla, Theodoros Damoulas, Sally Cripps

Semantic Conditioned Dynamic Modulation for Temporal Sentence Grounding in Videos

Yitian Yuan, Lin Ma, Jingwen Wang, Wei Liu, Wenwu Zhu

Pareto Multi-Task Learning

Xi Lin, Hui-Ling Zhen, Zhenhua Li, Sam Kwong, Qingfu Zhang

No-Regret Learning in Unknown Games with Correlated Payoffs

Pier Giuseppe Sessa, Ilija Bogunovic, Maryam Kamgarpour, Andreas Krause

Uncoupled Regression from Pairwise Comparison Data

Liyuan Xu, Junya Honda, Gang Niu, Masashi Sugiyama

Deliberative Explanations: visualizing network insecurities

Pei Wang, Nuno Nvasconcelos

MelGAN: Generative Adversarial Networks for Conditional Waveform Synthesis

Kundan Kumar, Rithesh Kumar, Thibault de Boissiere, Lucas Gestin, Wei Zhen Teoh

Image Captioning: Transforming Objects into Words

Simao Herdade, Armin Kappeler, Kofi Boakye, Joao Soares

Can SGD Learn Recurrent Neural Networks with Provable Generalization?

Zeyuan Allen-Zhu, Yuanzhi Li

Toward a Characterization of Loss Functions for Distribution Learning

Nika Haghtalab, Cameron Musco, Bo Waggoner

Updates of Equilibrium Prop Match Gradients of Backprop Through Time in an RNN with Static Input

Maxence Ernoult, Julie Grollier, Damien Querlioz, Yoshua Bengio, Benjamin Scellier

Multi-View Reinforcement Learning

Minne Li, Lisheng Wu, Jun Wang, Haitham Bou Ammar

Enhancing the Locality and Breaking the Memory Bottleneck of Transformer on Time Series Forecasting

Shiyang Li, Xiaoyong Jin, Yao Xuan, Xiyou Zhou, Wenhu Chen

Learning Perceptual Inference by Contrasting

Chi Zhang, Baoxiong Jia, Feng Gao, Yixin Zhu, Hongjing Lu

Levenshtein Transformer

Jiatao Gu, Changhan Wang, Junbo Zhao

Hyperparameter Learning via Distributional Transfer

Ho Chung Law, Peilin Zhao, Leung Sing Chan, Junzhou Huang, Dino Sejdinovic

Learning Data Manipulation for Augmentation and Weighting

Zhiting Hu, Bowen Tan, Ruslan Salakhutdinov, Tom M. Mitchell, Eric P. Xing

Privacy-Preserving Q-Learning with Functional Noise in Continuous Spaces

Baoxiang Wang, Nidhi Hegde

Graph Neural Tangent Kernel: Fusing Graph Neural Networks with Graph Kernels

Simon S Du, Kangcheng Hou, Ruslan Salakhutdinov, Barnabás Póczos, Ruosong Wang

E2-Train: Training State-of-the-art CNNs with Over 80% Energy Savings

Yue Wang, Ziyu Jiang, Xiaohan Chen, Pengfei Xu, Yang Zhao

Are deep ResNets provably better than linear predictors?

Chulhee Yun, Suvrit Sra, Ali Jadbabaie

Hybrid 8-bit Floating Point (HFP8) Training and Inference for Deep Neural Networks

Xiao Sun, Jungwook Choi, Chia-Yu Chen, Naigang Wang, Swagath Venkataramani

The Landscape of Non-convex Empirical Risk with Degenerate Population Risk

Shuang Li, Gongguo Tang, Michael B Wakin

Are sample means in multi-armed bandits positively or negatively biased?

Jaehyeok Shin, Aaditya Ramdas, Alessandro Rinaldo

Rapid Convergence of the Unadjusted Langevin Algorithm: Isoperimetry Suffices

Santosh Vempala, Andre Wibisono

McDiarmid-Type Inequalities for Graph-Dependent Variables and Stability Bounds

Rui (Ray) Zhang, Xingwu Liu, Yuyi Wang, Liwei Wang

HYPE: A Benchmark for Human eYe Perceptual Evaluation of Generative Models

Sharon Zhou, Mitchell Gordon, Ranjay Krishna, Austin Narcomey, Li F Fei-Fei

The Synthesis of XNOR Recurrent Neural Networks with Stochastic Logic

Arash Ardakani, Zhengyun Ji, Amir Ardakani, Warren Gross

Efficient characterization of electrically evoked responses for neural interfaces

Nishal Shah, Sasidhar Madugula, Pawel Hottowy, Alexander Sher, Alan Litke

Keeping Your Distance: Solving Sparse Reward Tasks Using Self-Balancing Shaped Rewards

Alexander Trott, Stephan Zheng, Caiming Xiong, Richard Socher

Multi-task Learning for Aggregated Data using Gaussian Processes

Fariba Yousefi, Michael T Smith, Mauricio Alvarez

Variational Denoising Network: Toward Blind Noise Modeling and Removal

Zongsheng Yue, Hongwei Yong, Qian Zhao, Deyu Meng, Lei Zhang

Unsupervised Scale-consistent Depth and Ego-motion Learning from Monocular Video

Jiawang Bian, Zhichao Li, Naiyan Wang, Huangying Zhan, Chunhua Shen

Approximation Ratios of Graph Neural Networks for Combinatorial Problems

Ryoma Sato, Makoto Yamada, Hisashi Kashima

Online Forecasting of Total-Variation-bounded Sequences

Dheeraj Baby, Yu-Xiang Wang

Learning and Generalization in Overparameterized Neural Networks, Going Beyond Two Layers

Zeyuan Allen-Zhu, Yuanzhi Li, Yingyu Liang

Gradient-based Adaptive Markov Chain Monte Carlo

Michalis Titsias, Petros Dellaportas

Multivariate Triangular Quantile Maps for Novelty Detection

Jingjing Wang, Sun Sun, Yaoliang Yu

Learning Imbalanced Datasets with Label-Distribution-Aware Margin Loss

Kaidi Cao, Colin Wei, Adrien Gaidon, Nikos Arechiga, Tengyu Ma

Solving Interpretable Kernel Dimensionality Reduction

Chieh Wu, Jared Miller, Yale Chang, Mario Sznaier, Jennifer Dy

Sampling Sketches for Concave Sublinear Functions of Frequencies

Edith Cohen, Ofir Geri

The Thermodynamic Variational Objective

Vaden Masrani, Tuan Anh Le, Frank Wood

Correlation in Extensive-Form Games: Saddle-Point Formulation and Benchmarks

Gabriele Farina, Chun Kai Ling, Fei Fang, Tuomas Sandholm

Pure Exploration with Multiple Correct Answers

Rémy Degenne, Wouter M. Koolen

Robustness to Adversarial Perturbations in Learning from Incomplete Data

Amir Najafi, Shin-ichi Maeda, Masanori Koyama, Takeru Miyato

Deep Leakage from Gradients

Ligeng Zhu, Zhijian Liu, Song Han

k-Means Clustering of Lines for Big Data

Yair Marom, Dan Feldman

Variance Reduced Policy Evaluation with Smooth Function Approximation

Hoi-To Wai, Mingyi Hong, Zhuoran Yang, Zhaoran Wang, Kexin Tang

Is Deeper Better only when Shallow is Good?

Eran Malach, Shai Shalev-shwartz

Globally Convergent Newton Methods for Ill-conditioned Generalized Self-concordant Losses

Ulysse Marteau-Ferey, Francis Bach, Alessandro Rudi

Learning New Tricks From Old Dogs: Multi-Source Transfer Learning From Pre-Trained Networks

Joshua Lee, Prasanna Sattigeri, Gregory Wornell

Learning to Learn By Self-Critique

Antreas Antoniou, Amos J. Storkey

Blind Super-Resolution Kernel Estimation using an Internal-GAN

Sefi Bell-Kligler, Assaf Shocher, Michal Irani

On Making Stochastic Classifiers Deterministic

Andrew Cotter, Maya Gupta, Harikrishna Narasimhan

When to Trust Your Model: Model-Based Policy Optimization

Michael Janner, Justin Fu, Marvin Zhang, Sergey Levine

Generating Diverse High-Fidelity Images with VQ-VAE-2

Ali Razavi, Aaron van den Oord, Oriol Vinyals

Universality and individuality in neural dynamics across large populations of recurrent networks

Niru Maheswaranathan, Alex Williams, Matthew Golub, Surya Ganguli, David Sussillo

Data Cleansing for Models Trained with SGD

Satoshi Hara, Atsushi Nitanda, Takanori Maehara

Sample Efficient Active Learning of Causal Trees

Kristjan Greenewald, Dmitriy Katz, Karthikeyan Shanmugam, Sara Magliacane, Murat Kocaoglu

An Accelerated Decentralized Stochastic Proximal Algorithm for Finite Sums

Hadrien Hendrikx, Francis Bach, Laurent Massoulié