NeurIPS 2020

1,898 papers

Least Squares Regression with Markovian Data: Fundamental Limits and Algorithms

Dheeraj Nagaraj, Xian Wu, Guy Bresler, Prateek Jain, Praneeth Netrapalli

End-to-End Learning and Intervention in Games

Jiayang Li, Jing Yu, Yu Nie, Zhaoran Wang

Learning to Detect Objects with a 1 Megapixel Event Camera

Etienne Perot, Pierre de Tournemire, Davide Nitti, Jonathan Masci, Amos Sironi

Finite-Time Analysis for Double Q-learning

Huaqing Xiong, Lin Zhao, Yingbin Liang, Wei Zhang

Numerically Solving Parametric Families of High-Dimensional Kolmogorov Partial Differential Equations via Deep Learning

Julius Berner, Markus Dablander, Philipp Grohs

Explicit Regularisation in Gaussian Noise Injections

Alexander Camuto, Matthew Willetts, Umut Simsekli, Stephen J. Roberts, Chris C Holmes

Optimal Variance Control of the Score-Function Gradient Estimator for Importance-Weighted Bounds

Valentin Liévin, Andrea Dittadi, Anders Christensen, Ole Winther

Self-Supervised Visual Representation Learning from Hierarchical Grouping

Xiao Zhang, Michael Maire

Relative gradient optimization of the Jacobian term in unsupervised deep learning

Luigi Gresele, Giancarlo Fissore, Adrián Javaloy, Bernhard Schölkopf, Aapo Hyvärinen

Simultaneously Learning Stochastic and Adversarial Episodic MDPs with Known Transition

Tiancheng Jin, Haipeng Luo

Convex optimization based on global lower second-order models

Nikita Doikov, Yurii Nesterov

Online Fast Adaptation and Knowledge Accumulation (OSAKA): a New Approach to Continual Learning

Massimo Caccia, Pau Rodriguez, Oleksiy Ostapenko, Fabrice Normandin, Min Lin

Node Classification on Graphs with Few-Shot Novel Labels via Meta Transformed Network Embedding

Lin Lan, Pinghui Wang, Xuefeng Du, Kaikai Song, Jing Tao

Gaussian Gated Linear Networks

David Budden, Adam Marblestone, Eren Sezener, Tor Lattimore, Gregory Wayne

Deep Reinforcement Learning with Stacked Hierarchical Attention for Text-based Games

Yunqiu Xu, Meng Fang, Ling Chen, Yali Du, Joey Tianyi Zhou

GAN Memory with No Forgetting

Yulai Cong, Miaoyun Zhao, Jianqiao Li, Sijia Wang, Lawrence Carin

Bongard-LOGO: A New Benchmark for Human-Level Concept Learning and Reasoning

Weili Nie, Zhiding Yu, Lei Mao, Ankit B Patel, Yuke Zhu

Conditioning and Processing: Techniques to Improve Information-Theoretic Generalization Bounds

Hassan Hafez-Kolahi, Zeinab Golgooni, Shohreh Kasaei, Mahdieh Soleymani

Latent Dynamic Factor Analysis of High-Dimensional Neural Recordings

Heejong Bong, Zongge Liu, Zhao Ren, Matthew Smith, Valerie Ventura

Estimating the Effects of Continuous-valued Interventions using Generative Adversarial Networks

Ioana Bica, James Jordon, Mihaela van der Schaar

Path Integral Based Convolution and Pooling for Graph Neural Networks

Zheng Ma, Junyu Xuan, Ming Li, Pietro Lió, Yuguang Wang

Greedy Optimization Provably Wins the Lottery: Logarithmic Number of Winning Tickets is Enough

Mao Ye, Lemeng Wu, Qiang Liu

A meta-learning approach to (re)discover plasticity rules that carve a desired function into a neural network

Basile Confavreux, Friedemann Zenke, Everton Agnes, Timothy Lillicrap, TIm Vogels

SoftFlow: Probabilistic Framework for Normalizing Flow on Manifolds

Hyeongju Kim, Hyeonseung Lee, Woo Hyun Kang, Joun Yeop Lee, Nam Soo Kim

Robustness Analysis of Non-Convex Stochastic Gradient Descent using Biased Expectations

Kevin Scaman, Cedric Malherbe

Bayesian Attention Modules

Xinjie Fan, Shujian Zhang, Bo Chen, Mingyuan Zhou

DeepSVG: A Hierarchical Generative Network for Vector Graphics Animation

Alexandre Carlier, Martin Danelljan, Alexandre Alahi, Radu Timofte

Cross-validation Confidence Intervals for Test Error

Pierre Bayle, Alexandre Bayle, Lucas Janson, Lester W. Mackey

On Learning Ising Models under Huber's Contamination Model

Adarsh Prasad, Vishwak Srinivasan, Sivaraman Balakrishnan, Pradeep K Ravikumar, Pradeep K. Ravikumar

Constrained episodic reinforcement learning in concave-convex and knapsack settings

Kianté Brantley, Miro Dudik, Thodoris Lykouris, Sobhan Miryoosefi, Max Simchowitz

Stochastic Normalization

Zhi Kou, Kaichao You, Mingsheng Long, Jianmin Wang

Patch2Self: Denoising Diffusion MRI with Self-Supervised Learning

Shreyas Fadnavis, Joshua Batson, Eleftherios Garyfallidis

Universal Domain Adaptation through Self Supervision

Kuniaki Saito, Donghyun Kim, Stan Sclaroff, Kate Saenko

Sub-linear Regret Bounds for Bayesian Optimisation in Unknown Search Spaces

Hung Tran-The, Sunil Gupta, Santu Rana, Huong Ha, Svetha Venkatesh

When Counterpoint Meets Chinese Folk Melodies

Nan Jiang, Sheng Jin, Zhiyao Duan, Changshui Zhang

Variational Amodal Object Completion

huan ling, David Acuna, Karsten Kreis, Seung Wook Kim, Sanja Fidler

Fast and Accurate k-means++ via Rejection Sampling

Vincent Cohen-Addad, Silvio Lattanzi, Ashkan Norouzi-Fard, Christian Sohler, Ola Svensson

Explore Aggressively, Update Conservatively: Stochastic Extragradient Methods with Variable Stepsize Scaling

Yu-Guan Hsieh, Franck Iutzeler, Jérôme Malick, Panayotis Mertikopoulos

Random Walk Graph Neural Networks

Giannis Nikolentzos, Michalis Vazirgiannis

Robust Pre-Training by Adversarial Contrastive Learning

Ziyu Jiang, Tianlong Chen, Ting Chen, Zhangyang Wang

Online Bayesian Persuasion

Matteo Castiglioni, Andrea Celli, Alberto Marchesi, Nicola Gatti

Learning Continuous System Dynamics from Irregularly-Sampled Partial Observations

Zijie Huang, Yizhou Sun, Wei Wang

An Efficient Adversarial Attack for Tree Ensembles

Chong Zhang, Huan Zhang, Cho-jui Hsieh

Sparse Spectrum Warped Input Measures for Nonstationary Kernel Learning

Anthony Tompkins, Rafael Oliveira, Fabio T Ramos

Improved Guarantees for k-means++ and k-means++ Parallel

Konstantin Makarychev, Aravind Reddy, Liren Shan

Compressing Images by Encoding Their Latent Representations with Relative Entropy Coding

Gergely Flamich, Marton Havasi, José Miguel Hernández-Lobato

Skeleton-bridged Point Completion: From Global Inference to Local Adjustment

Yinyu Nie, Yiqun Lin, Xiaoguang Han, Shihui Guo, Jian Chang

Bayesian Meta-Learning for the Few-Shot Setting via Deep Kernels

Massimiliano Patacchiola, Jack Turner, Elliot J. Crowley, Michael O'Boyle, Amos J. Storkey

Domain Generalization via Entropy Regularization

Shanshan Zhao, Mingming Gong, Tongliang Liu, Huan Fu, Dacheng Tao

Certifiably Adversarially Robust Detection of Out-of-Distribution Data

Julian Bitterwolf, Alexander Meinke, Matthias Hein

Attack of the Tails: Yes, You Really Can Backdoor Federated Learning

Hongyi Wang, Kartik Sreenivasan, Shashank Rajput, Harit Vishwakarma, Saurabh Agarwal

Coded Sequential Matrix Multiplication For Straggler Mitigation

Nikhil Krishnan Muralee Krishnan, Seyederfan Hosseini, Ashish Khisti

Understanding and Improving Fast Adversarial Training

Maksym Andriushchenko, Nicolas Flammarion

Batched Coarse Ranking in Multi-Armed Bandits

Nikolai Karpov, Qin Zhang

Variational Bayesian Unlearning

Quoc Phong Nguyen, Bryan Kian Hsiang Low, Patrick Jaillet

Inductive Quantum Embedding

Santosh Kumar Srivastava, Dinesh Khandelwal, Dhiraj Madan, Dinesh Garg, Hima Karanam

The Diversified Ensemble Neural Network

Shaofeng Zhang, Meng Liu, Junchi Yan

Shared Space Transfer Learning for analyzing multi-site fMRI data

Tony Muhammad Yousefnezhad, Alessandro Selvitella, Daoqiang Zhang, Andrew Greenshaw, Russell Greiner

Decentralized Langevin Dynamics for Bayesian Learning

Anjaly Parayil, He Bai, Jemin George, Prudhvi Gurram

PLLay: Efficient Topological Layer based on Persistent Landscapes

Kwangho Kim, Jisu KIM, Manzil Zaheer, Joon Kim, Frederic Chazal

On the linearity of large non-linear models: when and why the tangent kernel is constant

Chaoyue Liu, Libin Zhu, Misha Belkin

Neural encoding with visual attention

Meenakshi Khosla, Gia Ngo, Keith Jamison, Amy Kuceyeski, Mert Sabuncu

Learning to Utilize Shaping Rewards: A New Approach of Reward Shaping

Yujing Hu, Weixun Wang, Hangtian Jia, Yixiang Wang, Yingfeng Chen

Dark Experience for General Continual Learning: a Strong, Simple Baseline

Pietro Buzzega, Matteo Boschini, Angelo Porrello, Davide Abati, SIMONE CALDERARA

Non-Crossing Quantile Regression for Distributional Reinforcement Learning

Fan Zhou, Jianing Wang, Xingdong Feng

On the Expressiveness of Approximate Inference in Bayesian Neural Networks

Andrew Foong, David Burt, Yingzhen Li, Richard Turner

Few-shot Image Generation with Elastic Weight Consolidation

Yijun Li, Richard Zhang, Jingwan (Cynthia) Lu, Eli Shechtman

AdvFlow: Inconspicuous Black-box Adversarial Attacks using Normalizing Flows

Hadi Mohaghegh Dolatabadi, Sarah Erfani, Christopher Leckie

Beyond Perturbations: Learning Guarantees with Arbitrary Adversarial Test Examples

Shafi Goldwasser, Adam Tauman Kalai, Yael Kalai, Omar Montasser

Label-Aware Neural Tangent Kernel: Toward Better Generalization and Local Elasticity

Shuxiao Chen, Hangfeng He, Weijie Su

The Lottery Ticket Hypothesis for Pre-trained BERT Networks

Tianlong Chen, Jonathan Frankle, Shiyu Chang, Sijia Liu, Yang Zhang

Regret Bounds without Lipschitz Continuity: Online Learning with Relative-Lipschitz Losses

Yihan Zhou, Victor Sanches Portella, Mark Schmidt, Nicholas Harvey

Towards Scale-Invariant Graph-related Problem Solving by Iterative Homogeneous GNNs

Hao Tang, Zhiao Huang, Jiayuan Gu, Bao-Liang Lu, Hao Su

Hitting the High Notes: Subset Selection for Maximizing Expected Order Statistics

Aranyak Mehta, Uri Nadav, Alexandros Psomas, Aviad Rubinstein

Emergent Reciprocity and Team Formation from Randomized Uncertain Social Preferences

Bowen Baker

Promoting Coordination through Policy Regularization in Multi-Agent Deep Reinforcement Learning

Julien Roy, Paul Barde, Félix Harvey, Derek Nowrouzezahrai, Chris Pal

Consequences of Misaligned AI

Simon Zhuang, Dylan Hadfield-Menell

Disentangling Human Error from Ground Truth in Segmentation of Medical Images

Le Zhang, Ryutaro Tanno, Mou-Cheng Xu, Chen Jin, Joseph Jacob

Error Bounds of Imitating Policies and Environments

Tian Xu, Ziniu Li, Yang Yu

A Contour Stochastic Gradient Langevin Dynamics Algorithm for Simulations of Multi-modal Distributions

Wei Deng, Guang Lin, Faming Liang

Learning efficient task-dependent representations with synaptic plasticity

Colin Bredenberg, Eero P. Simoncelli, Cristina Savin

Adaptive Importance Sampling for Finite-Sum Optimization and Sampling with Decreasing Step-Sizes

Ayoub El Hanchi, David Stephens

Robust Sub-Gaussian Principal Component Analysis and Width-Independent Schatten Packing

Arun Jambulapati, Jerry Li, Kevin Tian

The Discrete Gaussian for Differential Privacy

Clément L Canonne, Gautam Kamath, Thomas Steinke

A Flexible Framework for Designing Trainable Priors with Adaptive Smoothing and Game Encoding

Bruno Lecouat, Jean Ponce, Julien Mairal

Neural Sparse Voxel Fields

Lingjie Liu, Jiatao Gu, Kyaw Zaw Lin, Tat-Seng Chua, Christian Theobalt

Collapsing Bandits and Their Application to Public Health Intervention

Aditya Mate, Jackson Killian, Haifeng Xu, Andrew Perrault, Milind Tambe

Sparse Weight Activation Training

Md Aamir Raihan, Tor Aamodt

Parametric Instance Classification for Unsupervised Visual Feature learning

Yue Cao, Zhenda Xie, Bin Liu, Yutong Lin, Zheng Zhang

Robustness of Bayesian Neural Networks to Gradient-Based Attacks

Ginevra Carbone, Matthew Wicker, Luca Laurenti, Andrea Patane', Luca Bortolussi

Online Convex Optimization Over Erdos-Renyi Random Networks

Jinlong Lei, Peng Yi, Yiguang Hong, Jie Chen, Guodong Shi

Calibrating CNNs for Lifelong Learning

Pravendra Singh, Vinay Kumar Verma, Pratik Mazumder, Lawrence Carin, Piyush Rai

Kernel Alignment Risk Estimator: Risk Prediction from Training Data

Arthur Jacot, Berfin Simsek, Francesco Spadaro, Clement Hongler, Franck Gabriel

A Unified Switching System Perspective and Convergence Analysis of Q-Learning Algorithms

Donghwan Lee, Niao He

StratLearner: Learning a Strategy for Misinformation Prevention in Social Networks

Guangmo Tong

A Ranking-based, Balanced Loss Function Unifying Classification and Localisation in Object Detection

Kemal Oksuz, Baris Can Cam, Emre Akbas, Sinan Kalkan

Bias no more: high-probability data-dependent regret bounds for adversarial bandits and MDPs

Chung-Wei Lee, Haipeng Luo, Chen-Yu Wei, Mengxiao Zhang

Improved Analysis of Clipping Algorithms for Non-convex Optimization

Bohang Zhang, Jikai Jin, Cong Fang, Liwei Wang

Markovian Score Climbing: Variational Inference with KL(p||q)

Christian Naesseth, Fredrik Lindsten, David M. Blei

Model Interpretability through the lens of Computational Complexity

Pablo Barceló, Mikaël Monet, Jorge Pérez, Bernardo Subercaseaux