NeurIPS 2019

1,428 papers

Ultrametric Fitting by Gradient Descent

Giovanni Chierchia, Benjamin Perret

Adversarial Self-Defense for Cycle-Consistent GANs

Dina Bashkirova, Ben Usman, Kate Saenko

Momentum-Based Variance Reduction in Non-Convex SGD

Ashok Cutkosky, Francesco Orabona

Control What You Can: Intrinsically Motivated Task-Planning Agent

Sebastian Blaes, Marin Vlastelica Pogančić, Jiajie Zhu, Georg Martius

Scene Representation Networks: Continuous 3D-Structure-Aware Neural Scene Representations

Vincent Sitzmann, Michael Zollhoefer, Gordon Wetzstein

Variational Temporal Abstraction

Taesup Kim, Sungjin Ahn, Yoshua Bengio

Off-Policy Evaluation via Off-Policy Classification

Alexander Irpan, Kanishka Rao, Konstantinos Bousmalis, Chris Harris, Julian Ibarz

Dual Variational Generation for Low Shot Heterogeneous Face Recognition

Chaoyou Fu, Xiang Wu, Yibo Hu, Huaibo Huang, Ran He

Quality Aware Generative Adversarial Networks

KANCHARLA PARIMALA, Sumohana Channappayya

Deep Active Learning with a Neural Architecture Search

Yonatan Geifman, Ran El-Yaniv

Practical Deep Learning with Bayesian Principles

Kazuki Osawa, Siddharth Swaroop, Mohammad Emtiyaz Khan, Anirudh Jain, Runa Eschenhagen

Kalman Filter, Sensor Fusion, and Constrained Regression: Equivalences and Insights

Maria Jahja, David Farrow, Roni Rosenfeld, Ryan J Tibshirani

Gate Decorator: Global Filter Pruning Method for Accelerating Deep Convolutional Neural Networks

Zhonghui You, Kun Yan, Jinmian Ye, Meng Ma, Ping Wang

Visualizing the PHATE of Neural Networks

Scott Gigante, Adam S Charles, Smita Krishnaswamy, Gal Mishne

Don't take it lightly: Phasing optical random projections with unknown operators

Sidharth Gupta, Remi Gribonval, Laurent Daudet, Ivan Dokmanić

Optimistic Distributionally Robust Optimization for Nonparametric Likelihood Approximation

Viet Anh Nguyen, Soroosh Shafieezadeh-Abadeh, Man-Chung Yue, Daniel Huhn, Wolfram Wiesemann

Online Continuous Submodular Maximization: From Full-Information to Bandit Feedback

Mingrui Zhang, Lin Chen, Hamed Hassani, Amin Karbasi

SGD on Neural Networks Learns Functions of Increasing Complexity

Dimitris Kalimeris, Gal Kaplun, Preetum Nakkiran, Benjamin Edelman, Tristan Yang

Inherent Tradeoffs in Learning Fair Representations

Han Zhao, Geoff Gordon

Elliptical Perturbations for Differential Privacy

Matthew Reimherr, Jordan Awan

Approximate Inference Turns Deep Networks into Gaussian Processes

Mohammad Emtiyaz Khan, Alexander Immer, Ehsan Abedi, Maciej Korzepa

No Pressure! Addressing the Problem of Local Minima in Manifold Learning Algorithms

Max Vladymyrov

Piecewise Strong Convexity of Neural Networks

Tristan Milne

Average Case Column Subset Selection for Entrywise ℓ_1-Norm Loss

Zhao Song, David Woodruff, Peilin Zhong

Learning to Predict Layout-to-image Conditional Convolutions for Semantic Image Synthesis

Xihui Liu, Guojun Yin, Jing Shao, Xiaogang Wang, hongsheng Li

Identification of Conditional Causal Effects under Markov Equivalence

Amin Jaber, Jiji Zhang, Elias Bareinboim

Neural Relational Inference with Fast Modular Meta-learning

Ferran Alet, Erica Weng, Tomás Lozano-Pérez, Leslie Pack Kaelbling

Learning GANs and Ensembles Using Discrepancy

Ben Adlam, Corinna Cortes, Mehryar Mohri, Ningshan Zhang

Controlling Neural Level Sets

Matan Atzmon, Niv Haim, Lior Yariv, Ofer Israelov, Haggai Maron

Invertible Convolutional Flow

Mahdi Karami, Dale Schuurmans, Jascha Sohl-dickstein, Laurent Dinh, Daniel Duckworth

muSSP: Efficient Min-cost Flow Algorithm for Multi-object Tracking

Congchao Wang, Yizhi Wang, Yinxue Wang, Chiung-Ting Wu, Guoqiang Yu

Distributed estimation of the inverse Hessian by determinantal averaging

Michal Derezinski, Michael W. Mahoney

A Communication Efficient Stochastic Multi-Block Alternating Direction Method of Multipliers

Hao Yu

Practical Differentially Private Top-k Selection with Pay-what-you-get Composition

David Durfee, Ryan M Rogers

Ease-of-Teaching and Language Structure from Emergent Communication

Fushan Li, Michael Bowling

Deep imitation learning for molecular inverse problems

Eric Jonas

Correlation Clustering with Adaptive Similarity Queries

Marco Bressan, Nicolò Cesa-bianchi, Andrea Paudice, Fabio Vitale

Fixing Implicit Derivatives: Trust-Region Based Learning of Continuous Energy Functions

Chris Russell, Matteo Toso, Neill Campbell

Two Generator Game: Learning to Sample via Linear Goodness-of-Fit Test

Lizhong Ding, Mengyang Yu, Li Liu, Fan Zhu, Yong Liu

A Fourier Perspective on Model Robustness in Computer Vision

Dong Yin, Raphael Gontijo Lopes, Jon Shlens, Ekin Dogus Cubuk, Justin Gilmer

Optimistic Regret Minimization for Extensive-Form Games via Dilated Distance-Generating Functions

Gabriele Farina, Christian Kroer, Tuomas Sandholm

On the Optimality of Perturbations in Stochastic and Adversarial Multi-armed Bandit Problems

Baekjin Kim, Ambuj Tewari

Learning Transferable Graph Exploration

Hanjun Dai, Yujia Li, Chenglong Wang, Rishabh Singh, Po-Sen Huang

Emergence of Object Segmentation in Perturbed Generative Models

Adam Bielski, Paolo Favaro

Neural Multisensory Scene Inference

Jae Hyun Lim, Pedro O O. Pinheiro, Negar Rostamzadeh, Chris Pal, Sungjin Ahn

Towards Practical Alternating Least-Squares for CCA

Zhiqiang Xu, Ping Li

Using Embeddings to Correct for Unobserved Confounding in Networks

Victor Veitch, Yixin Wang, David Blei

Efficient Regret Minimization Algorithm for Extensive-Form Correlated Equilibrium

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

Estimating Convergence of Markov chains with L-Lag Couplings

Niloy Biswas, Pierre E Jacob, Paul Vanetti

On Lazy Training in Differentiable Programming

Lénaïc Chizat, Edouard Oyallon, Francis Bach

Fast Parallel Algorithms for Statistical Subset Selection Problems

Sharon Qian, Yaron Singer

Provable Certificates for Adversarial Examples: Fitting a Ball in the Union of Polytopes

Matt Jordan, Justin Lewis, Alexandros G Dimakis

Learning Dynamics of Attention: Human Prior for Interpretable Machine Reasoning

Wonjae Kim, Yoonho Lee

Phase Transitions and Cyclic Phenomena in Bandits with Switching Constraints

David Simchi-Levi, Yunzong Xu

Online EXP3 Learning in Adversarial Bandits with Delayed Feedback

Ilai Bistritz, Zhengyuan Zhou, Xi Chen, Nicholas Bambos, Jose Blanchet

This Looks Like That: Deep Learning for Interpretable Image Recognition

Chaofan Chen, Oscar Li, Daniel Tao, Alina Barnett, Cynthia Rudin

SSRGD: Simple Stochastic Recursive Gradient Descent for Escaping Saddle Points

Zhize Li

A unified variance-reduced accelerated gradient method for convex optimization

Guanghui Lan, Zhize Li, Yi Zhou

Interlaced Greedy Algorithm for Maximization of Submodular Functions in Nearly Linear Time

Alan Kuhnle

Staying up to Date with Online Content Changes Using Reinforcement Learning for Scheduling

Andrey Kolobov, Yuval Peres, Cheng Lu, Eric J Horvitz

Nonparametric Contextual Bandits in Metric Spaces with Unknown Metric

Nirandika Wanigasekara, Christina Yu

Positive-Unlabeled Compression on the Cloud

Yixing Xu, Yunhe Wang, Hanting Chen, Kai Han, Chunjing XU

Distinguishing Distributions When Samples Are Strategically Transformed

Hanrui Zhang, Yu Cheng, Vincent Conitzer

Optimal Sparse Decision Trees

Xiyang Hu, Cynthia Rudin, Margo Seltzer

Metamers of neural networks reveal divergence from human perceptual systems

Jenelle Feather, Alex Durango, Ray Gonzalez, Josh McDermott

Invert to Learn to Invert

Patrick Putzky, Max Welling

Cross-sectional Learning of Extremal Dependence among Financial Assets

Xing Yan, Qi Wu, Wen Zhang

(Nearly) Efficient Algorithms for the Graph Matching Problem on Correlated Random Graphs

Boaz Barak, Chi-Ning Chou, Zhixian Lei, Tselil Schramm, Yueqi Sheng

Why Can't I Dance in the Mall? Learning to Mitigate Scene Bias in Action Recognition

Jinwoo Choi, Chen Gao, Joseph C. E. Messou, Jia-Bin Huang

The Impact of Regularization on High-dimensional Logistic Regression

Fariborz Salehi, Ehsan Abbasi, Babak Hassibi

Finite-time Analysis of Approximate Policy Iteration for the Linear Quadratic Regulator

Karl Krauth, Stephen Tu, Benjamin Recht

A Linearly Convergent Method for Non-Smooth Non-Convex Optimization on the Grassmannian with Applications to Robust Subspace and Dictionary Learning

Zhihui Zhu, Tianyu Ding, Daniel Robinson, Manolis Tsakiris, René Vidal

Coordinated hippocampal-entorhinal replay as structural inference

Talfan Evans, Neil Burgess

Sparse Logistic Regression Learns All Discrete Pairwise Graphical Models

Shanshan Wu, Sujay Sanghavi, Alexandros G Dimakis

Sliced Gromov-Wasserstein

Vayer Titouan, Rémi Flamary, Nicolas Courty, Romain Tavenard, Laetitia Chapel

Hyper-Graph-Network Decoders for Block Codes

Eliya Nachmani, Lior Wolf

Seeing the Wind: Visual Wind Speed Prediction with a Coupled Convolutional and Recurrent Neural Network

Jennifer Cardona, Michael Howland, John Dabiri

Acceleration via Symplectic Discretization of High-Resolution Differential Equations

Bin Shi, Simon S Du, Weijie Su, Michael I. Jordan, Michael I Jordan

First Exit Time Analysis of Stochastic Gradient Descent Under Heavy-Tailed Gradient Noise

Thanh Huy Nguyen, Umut Simsekli, Mert Gurbuzbalaban, Gaël RICHARD

Spatially Aggregated Gaussian Processes with Multivariate Areal Outputs

Yusuke Tanaka, Toshiyuki Tanaka, Tomoharu Iwata, Takeshi Kurashima, Maya Okawa

The Case for Evaluating Causal Models Using Interventional Measures and Empirical Data

Amanda Gentzel, Dan Garant, David Jensen

Global Convergence of Least Squares EM for Demixing Two Log-Concave Densities

Wei Qian, Yuqian Zhang, Yudong Chen

Multi-objective Bayesian optimisation with preferences over objectives

Majid Abdolshah, Alistair Shilton, Santu Rana, Sunil Gupta, Svetha Venkatesh

Neural Similarity Learning

Weiyang Liu, Zhen Liu, James M. Rehg, Le Song

On the Accuracy of Influence Functions for Measuring Group Effects

Pang Wei W Koh, Kai-Siang Ang, Hubert Teo, Percy Liang

Foundations of Comparison-Based Hierarchical Clustering

Debarghya Ghoshdastidar, Michaël Perrot, Ulrike Von Luxburg

Manifold denoising by Nonlinear Robust Principal Component Analysis

He Lyu, Ningyu Sha, Shuyang Qin, Ming Yan, Yuying Xie

On the (In)fidelity and Sensitivity of Explanations

Chih-Kuan Yeh, Cheng-Yu Hsieh, Arun Suggala, David I Inouye, Pradeep K Ravikumar

Almost Horizon-Free Structure-Aware Best Policy Identification with a Generative Model

Andrea Zanette, Mykel J Kochenderfer, Emma Brunskill

Generalization Bounds in the Predict-then-Optimize Framework

Othman El Balghiti, Adam N. Elmachtoub, Paul Grigas, Ambuj Tewari

Training Language GANs from Scratch

Cyprien de Masson d'Autume, Shakir Mohamed, Mihaela Rosca, Jack Rae

Geometry-Aware Neural Rendering

Joshua Tobin, Wojciech Zaremba, Pieter Abbeel

Stochastic Bandits with Context Distributions

Johannes Kirschner, Andreas Krause

Variational Graph Recurrent Neural Networks

Ehsan Hajiramezanali, Arman Hasanzadeh, Krishna Narayanan, Nick Duffield, Mingyuan Zhou

An adaptive nearest neighbor rule for classification

Akshay Balsubramani, Sanjoy Dasgupta, Yoav Freund, Shay Moran

A Stochastic Composite Gradient Method with Incremental Variance Reduction

Junyu Zhang, Lin Xiao

Region Mutual Information Loss for Semantic Segmentation

Shuai Zhao, Yang Wang, Zheng Yang, Deng Cai

Trust Region-Guided Proximal Policy Optimization

Yuhui Wang, Hao He, Xiaoyang Tan, Yaozhong Gan

Combining Generative and Discriminative Models for Hybrid Inference

Victor Garcia Satorras, Zeynep Akata, Max Welling

Learning Mixtures of Plackett-Luce Models from Structured Partial Orders

Zhibing Zhao, Lirong Xia