NeurIPS 2021

2,334 papers

R-Drop: Regularized Dropout for Neural Networks

xiaobo liang, Lijun Wu, Juntao Li, Yue Wang, Qi Meng

Deep Learning Through the Lens of Example Difficulty

Robert Baldock, Hartmut Maennel, Behnam Neyshabur

A Separation Result Between Data-oblivious and Data-aware Poisoning Attacks

Samuel Deng, Sanjam Garg, Somesh Jha, Saeed Mahloujifar, Mohammad Mahmoody

Implicit Finite-Horizon Approximation and Efficient Optimal Algorithms for Stochastic Shortest Path

Liyu Chen, Mehdi Jafarnia-Jahromi, Rahul Jain, Haipeng Luo

Validation Free and Replication Robust Volume-based Data Valuation

Xinyi Xu, Zhaoxuan Wu, Chuan Sheng Foo, Bryan Kian Hsiang Low

The Causal-Neural Connection: Expressiveness, Learnability, and Inference

Kevin Xia, Kai-Zhan Lee, Yoshua Bengio, Elias Bareinboim

Stochastic Bias-Reduced Gradient Methods

Hilal Asi, Yair Carmon, Arun Jambulapati, Yujia Jin, Aaron Sidford

Gradient-based Hyperparameter Optimization Over Long Horizons

Paul Micaelli, Amos J. Storkey

Learning to Simulate Self-driven Particles System with Coordinated Policy Optimization

Zhenghao Peng, Quanyi Li, Ka Ming Hui, Chunxiao Liu, Bolei Zhou

Object-Centric Representation Learning with Generative Spatial-Temporal Factorization

Nanbo Li, Muhammad Ahmed Raza, Wenbin Hu, Zhaole Sun, Robert Fisher

Extracting Deformation-Aware Local Features by Learning to Deform

Guilherme Potje, Renato Martins, Felipe Chamone, Erickson Nascimento

Information is Power: Intrinsic Control via Information Capture

Nicholas Rhinehart, Jenny Wang, Glen Berseth, John Co-Reyes, Danijar Hafner

Risk Monotonicity in Statistical Learning

Zakaria Mhammedi

Dynamic influence maximization

Binghui Peng

Asymptotics of the Bootstrap via Stability with Applications to Inference with Model Selection

Morgane Austern, Vasilis Syrgkanis

Neural-PIL: Neural Pre-Integrated Lighting for Reflectance Decomposition

Mark Boss, Varun Jampani, Raphael Braun, Ce Liu, Jonathan Barron

Few-Shot Data-Driven Algorithms for Low Rank Approximation

Piotr Indyk, Tal Wagner, David Woodruff

Adversarial Feature Desensitization

Pouya Bashivan, Reza Bayat, Adam Ibrahim, Kartik Ahuja, Mojtaba Faramarzi

Universal Graph Convolutional Networks

Di Jin, Zhizhi Yu, Cuiying Huo, Rui Wang, Xiao Wang

Independent Prototype Propagation for Zero-Shot Compositionality

Frank Ruis, Gertjan Burghouts, Doina Bucur

Recurrence along Depth: Deep Convolutional Neural Networks with Recurrent Layer Aggregation

Jingyu Zhao, Yanwen Fang, Guodong Li

Scalable Bayesian GPFA with automatic relevance determination and discrete noise models

Kristopher Jensen, Ta-Chu Kao, Jasmine Stone, Guillaume Hennequin

Equivariant Manifold Flows

Isay Katsman, Aaron Lou, Derek Lim, Qingxuan Jiang, Ser Nam Lim

Drop, Swap, and Generate: A Self-Supervised Approach for Generating Neural Activity

Ran Liu, Mehdi Azabou, Max Dabagia, Chi-Heng Lin, Mohammad Gheshlaghi azar

Emergent Discrete Communication in Semantic Spaces

Mycal Tucker, Huao Li, Siddharth Agrawal, Dana Hughes, Katia Sycara

Local Differential Privacy for Regret Minimization in Reinforcement Learning

Evrard Garcelon, Vianney Perchet, Ciara Pike-Burke, Matteo Pirotta

Dynamic Causal Bayesian Optimization

Virginia Aglietti, Neil Dhir, Javier Gonzalez, Theodoros Damoulas

Parallelizing Thompson Sampling

Amin Karbasi, Vahab Mirrokni, Mohammad Shadravan

Exploiting Data Sparsity in Secure Cross-Platform Social Recommendation

Jinming Cui, Chaochao Chen, Lingjuan Lyu, Carl Yang, Wang Li

Revenue maximization via machine learning with noisy data

Ellen Vitercik, Tom Yan

Curriculum Design for Teaching via Demonstrations: Theory and Applications

Gaurav Yengera, Rati Devidze, Parameswaran Kamalaruban, Adish Singla

Kernel Identification Through Transformers

Fergus Simpson, Ian Davies, Vidhi Lalchand, Alessandro Vullo, Nicolas Durrande

Scalable Quasi-Bayesian Inference for Instrumental Variable Regression

Ziyu Wang, Yuhao Zhou, Tongzheng Ren, Jun Zhu

Modality-Agnostic Topology Aware Localization

Farhad Ghazvinian Zanjani, Ilia Karmanov, Hanno Ackermann, Daniel Dijkman, Simone Merlin

CO-PILOT: COllaborative Planning and reInforcement Learning On sub-Task curriculum

Shuang Ao, Tianyi Zhou, Guodong Long, Qinghua Lu, Liming Zhu

Efficient Mirror Descent Ascent Methods for Nonsmooth Minimax Problems

Feihu Huang, Xidong Wu, Heng Huang

Learning Collaborative Policies to Solve NP-hard Routing Problems

Minsu Kim, Jinkyoo Park, joungho kim

Online learning in MDPs with linear function approximation and bandit feedback.

Gergely Neu, Julia Olkhovskaya

Faster Matchings via Learned Duals

Michael Dinitz, Sungjin Im, Thomas Lavastida, Benjamin Moseley, Sergei Vassilvitskii

Generalization Bounds for (Wasserstein) Robust Optimization

Yang An, RUI GAO

NTopo: Mesh-free Topology Optimization using Implicit Neural Representations

Jonas Zehnder, Yue Li, Stelian Coros, Bernhard Thomaszewski

Dynaboard: An Evaluation-As-A-Service Platform for Holistic Next-Generation Benchmarking

Zhiyi Ma, Kawin Ethayarajh, Tristan Thrush, Somya Jain, Ledell Wu

Pareto-Optimal Learning-Augmented Algorithms for Online Conversion Problems

Bo Sun, Russell Lee, Mohammad Hajiesmaili, Adam Wierman, Danny Tsang

K-Net: Towards Unified Image Segmentation

Wenwei Zhang, Jiangmiao Pang, Kai Chen, Chen Change Loy

Online Learning in Periodic Zero-Sum Games

Tanner Fiez, Ryann Sim, Stratis Skoulakis, Georgios Piliouras, Lillian Ratliff

Believe What You See: Implicit Constraint Approach for Offline Multi-Agent Reinforcement Learning

Yiqin Yang, Xiaoteng Ma, Chenghao Li, Zewu Zheng, Qiyuan Zhang

Non-Gaussian Gaussian Processes for Few-Shot Regression

Marcin Sendera, Jacek Tabor, Aleksandra Nowak, Andrzej Bedychaj, Massimiliano Patacchiola

Escaping Saddle Points with Compressed SGD

Dmitrii Avdiukhin, Grigory Yaroslavtsev

Mitigating Forgetting in Online Continual Learning with Neuron Calibration

Haiyan Yin, Peng Yang, Ping Li

On the Estimation Bias in Double Q-Learning

Zhizhou Ren, Guangxiang Zhu, Hao Hu, Beining Han, Jianglun Chen

Latent Matters: Learning Deep State-Space Models

Alexej Klushyn, Richard Kurle, Maximilian Soelch, Botond Cseke, Patrick van der Smagt

Reliable Estimation of KL Divergence using a Discriminator in Reproducing Kernel Hilbert Space

Sandesh Ghimire, Aria Masoomi, Jennifer Dy

Distributed Zero-Order Optimization under Adversarial Noise

Arya Akhavan, Massimiliano Pontil, Alexandre Tsybakov

List-Decodable Mean Estimation in Nearly-PCA Time

Ilias Diakonikolas, Daniel Kane, Daniel Kongsgaard, Jerry Li, Kevin Tian

Towards understanding retrosynthesis by energy-based models

Ruoxi Sun, Hanjun Dai, Li Li, Steven Kearnes, Bo Dai

Infinite Time Horizon Safety of Bayesian Neural Networks

Mathias Lechner, Đorđe Žikelić, Krishnendu Chatterjee, Thomas Henzinger

Spectral embedding for dynamic networks with stability guarantees

Ian Gallagher, Andrew Jones, Patrick Rubin-Delanchy

Learning Gaussian Mixtures with Generalized Linear Models: Precise Asymptotics in High-dimensions

Bruno Loureiro, Gabriele Sicuro, Cedric Gerbelot, Alessandro Pacco, Florent Krzakala

Generalization Error Rates in Kernel Regression: The Crossover from the Noiseless to Noisy Regime

Hugo Cui, Bruno Loureiro, Florent Krzakala, Lenka Zdeborová

Recursive Causal Structure Learning in the Presence of Latent Variables and Selection Bias

Sina Akbari, Ehsan Mokhtarian, AmirEmad Ghassami, Negar Kiyavash

Contrastively Disentangled Sequential Variational Autoencoder

Junwen Bai, Weiran Wang, Carla P. Gomes

Parameterized Knowledge Transfer for Personalized Federated Learning

Jie Zhang, Song Guo, Xiaosong Ma, Haozhao Wang, Wenchao Xu

A single gradient step finds adversarial examples on random two-layers neural networks

Sébastien Bubeck, Yeshwanth Cherapanamjeri, Gauthier Gidel, Remi Tachet des Combes

An Online Method for A Class of Distributionally Robust Optimization with Non-convex Objectives

Qi Qi, Zhishuai Guo, Yi Xu, Rong Jin, Tianbao Yang

Credit Assignment Through Broadcasting a Global Error Vector

David Clark, L F Abbott, SueYeon Chung

Differentiable Quality Diversity

Matthew Fontaine, Stefanos Nikolaidis

Compositional Reinforcement Learning from Logical Specifications

Kishor Jothimurugan, Suguman Bansal, Osbert Bastani, Rajeev Alur

Meta-Adaptive Nonlinear Control: Theory and Algorithms

Guanya Shi, Kamyar Azizzadenesheli, Michael O'Connell, Soon-Jo Chung, Yisong Yue

The Many Faces of Adversarial Risk

Muni Sreenivas Pydi, Varun Jog

Fast Projection onto the Capped Simplex with Applications to Sparse Regression in Bioinformatics

Man Shun Ang, Jianzhu Ma, Nianjun Liu, Kun Huang, Yijie Wang

Neural Hybrid Automata: Learning Dynamics With Multiple Modes and Stochastic Transitions

Michael Poli, Stefano Massaroli, Luca Scimeca, Sanghyuk Chun, Seong Joon Oh

Baby Intuitions Benchmark (BIB): Discerning the goals, preferences, and actions of others

Kanishk Gandhi, Gala Stojnic, Brenden M Lake, Moira R Dillon

Practical Near Neighbor Search via Group Testing

Joshua Engels, Benjamin Coleman, Anshumali Shrivastava

On Provable Benefits of Depth in Training Graph Convolutional Networks

Weilin Cong, Morteza Ramezani, Mehrdad Mahdavi

Low-Fidelity Video Encoder Optimization for Temporal Action Localization

Mengmeng Xu, Juan Manuel Perez Rua, Xiatian Zhu, Bernard Ghanem, Brais Martinez

Sparse Training via Boosting Pruning Plasticity with Neuroregeneration

Shiwei Liu, Tianlong Chen, Xiaohan Chen, Zahra Atashgahi, Lu Yin

Sparse is Enough in Scaling Transformers

Sebastian Jaszczur, Aakanksha Chowdhery, Afroz Mohiuddin, LUKASZ KAISER, Wojciech Gajewski

Efficient methods for Gaussian Markov random fields under sparse linear constraints

David Bolin, Jonas Wallin

A Kernel-based Test of Independence for Cluster-correlated Data

Hongjiao Liu, Anna Plantinga, Yunhua Xiang, Michael Wu

Robust Implicit Networks via Non-Euclidean Contractions

Saber Jafarpour, Alexander Davydov, Anton Proskurnikov, Francesco Bullo

Can fMRI reveal the representation of syntactic structure in the brain?

Aniketh Janardhan Reddy, Leila Wehbe

Co-Adaptation of Algorithmic and Implementational Innovations in Inference-based Deep Reinforcement Learning

Hiroki Furuta, Tadashi Kozuno, Tatsuya Matsushima, Yutaka Matsuo, Shixiang (Shane) Gu

The Value of Information When Deciding What to Learn

Dilip Arumugam, Benjamin Van Roy

Calibration and Consistency of Adversarial Surrogate Losses

Pranjal Awasthi, Natalie Frank, Anqi Mao, Mehryar Mohri, Yutao Zhong

How does a Neural Network's Architecture Impact its Robustness to Noisy Labels?

Jingling Li, Mozhi Zhang, Keyulu Xu, John Dickerson, Jimmy Ba

TriBERT: Human-centric Audio-visual Representation Learning

Tanzila Rahman, Mengyu Yang, Leonid Sigal

A Little Robustness Goes a Long Way: Leveraging Robust Features for Targeted Transfer Attacks

Jacob Springer, Melanie Mitchell, Garrett Kenyon

Non-Asymptotic Analysis for Two Time-scale TDC with General Smooth Function Approximation

Yue Wang, Shaofeng Zou, Yi Zhou

Efficient Active Learning for Gaussian Process Classification by Error Reduction

Guang Zhao, Edward Dougherty, Byung-Jun Yoon, Francis Alexander, Xiaoning Qian

Graph Neural Networks with Adaptive Residual

Xiaorui Liu, Jiayuan Ding, Wei Jin, Han Xu, Yao Ma

Variational Model Inversion Attacks

Kuan-Chieh Wang, YAN FU, Ke Li, Ashish Khisti, Richard S. Zemel

Align before Fuse: Vision and Language Representation Learning with Momentum Distillation

Junnan Li, Ramprasaath Selvaraju, Akhilesh Gotmare, Shafiq Joty, Caiming Xiong

Variational Automatic Curriculum Learning for Sparse-Reward Cooperative Multi-Agent Problems

Jiayu Chen, Yuanxin Zhang, Yuanfan Xu, Huimin Ma, Huazhong Yang

MADE: Exploration via Maximizing Deviation from Explored Regions

Tianjun Zhang, Paria Rashidinejad, Jiantao Jiao, Yuandong Tian, Joseph E Gonzalez

Mean-based Best Arm Identification in Stochastic Bandits under Reward Contamination

Arpan Mukherjee, Ali Tajer, Pin-Yu Chen, Payel Das

(Implicit)^2: Implicit Layers for Implicit Representations

Zhichun Huang, Shaojie Bai, J. Zico Kolter

Why Spectral Normalization Stabilizes GANs: Analysis and Improvements

Zinan Lin, Vyas Sekar, Giulia Fanti

Novel Upper Bounds for the Constrained Most Probable Explanation Task

Tahrima Rahman, Sara Rouhani, Vibhav Gogate

3DP3: 3D Scene Perception via Probabilistic Programming

Nishad Gothoskar, Marco Cusumano-Towner, Ben Zinberg, Matin Ghavamizadeh, Falk Pollok

Conic Blackwell Algorithm: Parameter-Free Convex-Concave Saddle-Point Solving

Julien Grand-Clément, Christian Kroer