NeurIPS 2019

1,428 papers

Diffeomorphic Temporal Alignment Nets

Ron A Shapira Weber, Matan Eyal, Nicki Skafte, Oren Shriki, Oren Freifeld

A Refined Margin Distribution Analysis for Forest Representation Learning

Shen-Huan Lyu, Liang Yang, Zhi-Hua Zhou

Convergent Policy Optimization for Safe Reinforcement Learning

Ming Yu, Zhuoran Yang, Mladen Kolar, Zhaoran Wang

The Functional Neural Process

Christos Louizos, Xiahan Shi, Klamer Schutte, Max Welling

G2SAT: Learning to Generate SAT Formulas

Jiaxuan You, Haoze Wu, Clark Barrett, Raghuram Ramanujan, Jure Leskovec

Unsupervised Learning of Object Keypoints for Perception and Control

Tejas D Kulkarni, Ankush Gupta, Catalin Ionescu, Sebastian Borgeaud, Malcolm Reynolds

CNN^{2}: Viewpoint Generalization via a Binocular Vision

Wei-Da Chen, Shan-Hung (Brandon) Wu

Yanis Bahroun, Dmitri Chklovskii, Anirvan Sengupta

Multilabel reductions: what is my loss optimising?

Aditya K Menon, Ankit Singh Rawat, Sashank Reddi, Sanjiv Kumar

Distribution oblivious, risk-aware algorithms for multi-armed bandits with unbounded rewards

Anmol Kagrecha, Jayakrishnan Nair, Krishna Jagannathan

PowerSGD: Practical Low-Rank Gradient Compression for Distributed Optimization

Thijs Vogels, Sai Praneeth Karimireddy, Martin Jaggi

Subquadratic High-Dimensional Hierarchical Clustering

Amir Abboud, Vincent Cohen-Addad, Hussein Houdrouge

On the Transfer of Inductive Bias from Simulation to the Real World: a New Disentanglement Dataset

Muhammad Waleed Gondal, Manuel Wuthrich, Djordje Miladinovic, Francesco Locatello, Martin Breidt

Initialization of ReLUs for Dynamical Isometry

Rebekka Burkholz, Alina Dubatovka

Quaternion Knowledge Graph Embeddings

SHUAI ZHANG, Yi Tay, Lina Yao, Qi Liu

Reverse engineering recurrent networks for sentiment classification reveals line attractor dynamics

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

Approximating the Permanent by Sampling from Adaptive Partitions

Jonathan Kuck, Tri Dao, Hamid Rezatofighi, Ashish Sabharwal, Stefano Ermon

Ordered Memory

Yikang Shen, Shawn Tan, Arian Hosseini, Zhouhan Lin, Alessandro Sordoni

Differentiable Ranking and Sorting using Optimal Transport

Marco Cuturi, Olivier Teboul, Jean-philippe Vert

Identifying Causal Effects via Context-specific Independence Relations

Santtu Tikka, Antti Hyttinen, Juha Karvanen

Defense Against Adversarial Attacks Using Feature Scattering-based Adversarial Training

Haichao Zhang, Jianyu Wang

Cross-channel Communication Networks

Jianwei Yang, Zhile Ren, Chuang Gan, Hongyuan Zhu, Devi Parikh

Scalable Structure Learning of Continuous-Time Bayesian Networks from Incomplete Data

Dominik Linzner, Michael Schmidt, Heinz Koeppl

Unsupervised learning of object structure and dynamics from videos

Matthias Minderer, Chen Sun, Ruben Villegas, Forrester Cole, Kevin P. Murphy

Missing Not at Random in Matrix Completion: The Effectiveness of Estimating Missingness Probabilities Under a Low Nuclear Norm Assumption

Wei Ma, George H Chen

GNNExplainer: Generating Explanations for Graph Neural Networks

Zhitao Ying, Dylan Bourgeois, Jiaxuan You, Marinka Zitnik, Jure Leskovec

Modelling heterogeneous distributions with an Uncountable Mixture of Asymmetric Laplacians

Axel Brando, Jose A Rodriguez, Jordi Vitria, Alberto Rubio Muñoz

Polynomial Cost of Adaptation for X-Armed Bandits

Hedi Hadiji

Adaptive Cross-Modal Few-shot Learning

Chen Xing, Negar Rostamzadeh, Boris Oreshkin, Pedro O O. Pinheiro

LCA: Loss Change Allocation for Neural Network Training

Janice Lan, Rosanne Liu, Hattie Zhou, Jason Yosinski

Bias Correction of Learned Generative Models using Likelihood-Free Importance Weighting

Aditya Grover, Jiaming Song, Ashish Kapoor, Kenneth Tran, Alekh Agarwal

Offline Contextual Bandits with High Probability Fairness Guarantees

Blossom Metevier, Stephen Giguere, Sarah Brockman, Ari Kobren, Yuriy Brun

Ask not what AI can do, but what AI should do: Towards a framework of task delegability

Brian Lubars, Chenhao Tan

A Universally Optimal Multistage Accelerated Stochastic Gradient Method

Necdet Serhat Aybat, Alireza Fallah, Mert Gurbuzbalaban, Asuman Ozdaglar

Thinning for Accelerating the Learning of Point Processes

Tianbo Li, Yiping Ke

Recurrent Kernel Networks

Dexiong Chen, Laurent Jacob, Julien Mairal

Doubly-Robust Lasso Bandit

Gi-Soo Kim, Myunghee Cho Paik

Improved Regret Bounds for Bandit Combinatorial Optimization

Shinji Ito, Daisuke Hatano, Hanna Sumita, Kei Takemura, Takuro Fukunaga

Unsupervised Curricula for Visual Meta-Reinforcement Learning

Allan Jabri, Kyle Hsu, Abhishek Gupta, Ben Eysenbach, Sergey Levine

Neural Machine Translation with Soft Prototype

Yiren Wang, Yingce Xia, Fei Tian, Fei Gao, Tao Qin

Flexible Modeling of Diversity with Strongly Log-Concave Distributions

Joshua Robinson, Suvrit Sra, Stefanie Jegelka

Variational Bayesian Optimal Experimental Design

Adam Foster, Martin Jankowiak, Elias Bingham, Paul Horsfall, Yee Whye Teh

Cascade RPN: Delving into High-Quality Region Proposal Network with Adaptive Convolution

Thang Vu, Hyunjun Jang, Trung X. Pham, Chang Yoo

Assessing Disparate Impact of Personalized Interventions: Identifiability and Bounds

Nathan Kallus, Angela Zhou

Dimension-Free Bounds for Low-Precision Training

Zheng Li, Christopher M De Sa

Sim2real transfer learning for 3D human pose estimation: motion to the rescue

Carl Doersch, Andrew Zisserman

Co-Generation with GANs using AIS based HMC

Tiantian Fang, Alexander Schwing

Reflection Separation using a Pair of Unpolarized and Polarized Images

Youwei Lyu, Zhaopeng Cui, Si Li, Marc Pollefeys, Boxin Shi

Manifold-regression to predict from MEG/EEG brain signals without source modeling

David Sabbagh, Pierre Ablin, Gael Varoquaux, Alexandre Gramfort, Denis A. Engemann

Making the Cut: A Bandit-based Approach to Tiered Interviewing

Candice Schumann, Zhi Lang, Jeffrey Foster, John Dickerson

Learning Deterministic Weighted Automata with Queries and Counterexamples

Gail Weiss, Yoav Goldberg, Eran Yahav

On Testing for Biases in Peer Review

Ivan Stelmakh, Nihar Shah, Aarti Singh

Learning Disentangled Representation for Robust Person Re-identification

Chanho Eom, Bumsub Ham

Cross-Modal Learning with Adversarial Samples

CHAO LI, Shangqian Gao, Cheng Deng, De Xie, Wei Liu

Learning elementary structures for 3D shape generation and matching

Theo Deprelle, Thibault Groueix, Matthew Fisher, Vladimir Kim, Bryan Russell

Guided Meta-Policy Search

Russell Mendonca, Abhishek Gupta, Rosen Kralev, Pieter Abbeel, Sergey Levine

ResNets Ensemble via the Feynman-Kac Formalism to Improve Natural and Robust Accuracies

Bao Wang, Zuoqiang Shi, Stanley Osher

Deep Signature Transforms

Patrick Kidger, Patric Bonnier, Imanol Perez Arribas, Cristopher Salvi, Terry Lyons

Fast Decomposable Submodular Function Minimization using Constrained Total Variation

Senanayak Sesh Kumar Karri, Francis Bach, Thomas Pock

Deep Random Splines for Point Process Intensity Estimation of Neural Population Data

Gabriel Loaiza-Ganem, Sean Perkins, Karen Schroeder, Mark Churchland, John P. Cunningham

Fast Sparse Group Lasso

Yasutoshi Ida, Yasuhiro Fujiwara, Hisashi Kashima

Qsparse-local-SGD: Distributed SGD with Quantization, Sparsification and Local Computations

Debraj Basu, Deepesh Data, Can Karakus, Suhas Diggavi

Compiler Auto-Vectorization with Imitation Learning

Charith Mendis, Cambridge Yang, Yewen Pu, Dr.Saman Amarasinghe, Michael Carbin

Learn, Imagine and Create: Text-to-Image Generation from Prior Knowledge

Tingting Qiao, Jing Zhang, Duanqing Xu, Dacheng Tao

Comparing Unsupervised Word Translation Methods Step by Step

Mareike Hartmann, Yova Kementchedjhieva, Anders Søgaard

Exact Combinatorial Optimization with Graph Convolutional Neural Networks

Maxime Gasse, Didier Chetelat, Nicola Ferroni, Laurent Charlin, Andrea Lodi

Bandits with Feedback Graphs and Switching Costs

Raman Arora, Teodor Vanislavov Marinov, Mehryar Mohri

Kernel Truncated Randomized Ridge Regression: Optimal Rates and Low Noise Acceleration

Kwang-Sung Jun, Ashok Cutkosky, Francesco Orabona

Consistency-based Semi-supervised Learning for Object detection

Jisoo Jeong, Seungeui Lee, Jeesoo Kim, Nojun Kwak

Re-examination of the Role of Latent Variables in Sequence Modeling

Guokun Lai, Zihang Dai, Yiming Yang, Shinjae Yoo

Learning Object Bounding Boxes for 3D Instance Segmentation on Point Clouds

Bo Yang, Jianan Wang, Ronald Clark, Qingyong Hu, Sen Wang

Social-BiGAT: Multimodal Trajectory Forecasting using Bicycle-GAN and Graph Attention Networks

Vineet Kosaraju, Amir Sadeghian, Roberto Martín-Martín, Ian Reid, Hamid Rezatofighi

Efficient Graph Generation with Graph Recurrent Attention Networks

Renjie Liao, Yujia Li, Yang Song, Shenlong Wang, Will Hamilton

Learning step sizes for unfolded sparse coding

Pierre Ablin, Thomas Moreau, Mathurin Massias, Alexandre Gramfort

Self-supervised GAN: Analysis and Improvement with Multi-class Minimax Game

Ngoc-Trung Tran, Viet-Hung Tran, Bao-Ngoc Nguyen, Linxiao Yang, Ngai-Man (Man) Cheung

Quadratic Video Interpolation

Xiangyu Xu, Li Siyao, Wenxiu Sun, Qian Yin, Ming-Hsuan Yang

Fixing the train-test resolution discrepancy

Hugo Touvron, Andrea Vedaldi, Matthijs Douze, Herve Jegou

Locally Private Learning without Interaction Requires Separation

Amit Daniely, Vitaly Feldman

Discovering Neural Wirings

Mitchell Wortsman, Ali Farhadi, Mohammad Rastegari

Data-driven Estimation of Sinusoid Frequencies

Gautier Izacard, Sreyas Mohan, Carlos Fernandez-Granda

Program Synthesis and Semantic Parsing with Learned Code Idioms

Eui Chul Shin, Miltiadis Allamanis, Marc Brockschmidt, Alex Polozov

Intrinsic dimension of data representations in deep neural networks

Alessio Ansuini, Alessandro Laio, Davide Zoccolan, Jakob H. Macke, Jakob H Macke

Generalization Bounds of Stochastic Gradient Descent for Wide and Deep Neural Networks

Yuan Cao, Quanquan Gu

DualDICE: Behavior-Agnostic Estimation of Discounted Stationary Distribution Corrections

Ofir Nachum, Yinlam Chow, Bo Dai, Lihong Li

A Primal Dual Formulation For Deep Learning With Constraints

Yatin Nandwani, Abhishek Pathak, Mausam, Parag Singla

Multi-label Co-regularization for Semi-supervised Facial Action Unit Recognition

Xuesong Niu, Hu Han, Shiguang Shan, Xilin Chen

Self-attention with Functional Time Representation Learning

Da Xu, Chuanwei Ruan, Evren Korpeoglu, Sushant Kumar, Kannan Achan

STAR-Caps: Capsule Networks with Straight-Through Attentive Routing

Karim Ahmed, Lorenzo Torresani

Provable Non-linear Inductive Matrix Completion

Kai Zhong, Zhao Song, Prateek Jain, Inderjit S Dhillon

Robustness Verification of Tree-based Models

Hongge Chen, Huan Zhang, Si Si, Yang Li, Duane Boning

On Human-Aligned Risk Minimization

Liu Leqi, Adarsh Prasad, Pradeep K Ravikumar

KerGM: Kernelized Graph Matching

Zhen Zhang, Yijian Xiang, Lingfei Wu, Bing Xue, Arye Nehorai

Error Correcting Output Codes Improve Probability Estimation and Adversarial Robustness of Deep Neural Networks

Gunjan Verma, Ananthram Swami

A Unifying Framework for Spectrum-Preserving Graph Sparsification and Coarsening

Lee Gunderson, Gecia Bravo-Hermsdorff, Gecia Bravo Hermsdorff

Towards closing the gap between the theory and practice of SVRG

Othmane Sebbouh, Nidham Gazagnadou, Samy Jelassi, Francis Bach, Robert Gower

Bayesian Optimization with Unknown Search Space

Huong Ha, Santu Rana, Sunil Gupta, Thanh Nguyen, Hung Tran-The

Break the Ceiling: Stronger Multi-scale Deep Graph Convolutional Networks

Sitao Luan, Mingde Zhao, Xiao-Wen Chang, Doina Precup

Band-Limited Gaussian Processes: The Sinc Kernel

Felipe Tobar

Gaussian-Based Pooling for Convolutional Neural Networks

Takumi Kobayashi

Divergence-Augmented Policy Optimization

Qing Wang, Yingru Li, Jiechao Xiong, Tong Zhang