NeurIPS 2022

2,834 papers

Tenrec: A Large-scale Multipurpose Benchmark Dataset for Recommender Systems

Guanghu Yuan, Fajie Yuan, Yudong Li, Beibei Kong, Shujie Li

Estimating and Explaining Model Performance When Both Covariates and Labels Shift

Lingjiao Chen, Matei Zaharia, James Y Zou

Improving Multi-Task Generalization via Regularizing Spurious Correlation

Ziniu Hu, Zhe Zhao, Xinyang Yi, Tiansheng Yao, Lichan Hong

Follow-the-Perturbed-Leader for Adversarial Markov Decision Processes with Bandit Feedback

Yan Dai, Haipeng Luo, Liyu Chen

MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields

Ilyes Batatia, David P Kovacs, Gregor Simm, Christoph Ortner, Gabor Csanyi

Identification, Amplification and Measurement: A bridge to Gaussian Differential Privacy

Yi Liu, Ke Sun, Bei Jiang, Linglong Kong

Learning Long-Term Crop Management Strategies with CyclesGym

Matteo Turchetta, Luca Corinzia, Scott Sussex, Amanda Burton, Juan Herrera

Wasserstein K-means for clustering probability distributions

Yubo Zhuang, Xiaohui Chen, Yun Yang

Split-kl and PAC-Bayes-split-kl Inequalities for Ternary Random Variables

Yi-Shan Wu, Yevgeny Seldin

Learning low-dimensional generalizable natural features from retina using a U-net

Siwei Wang, Benjamin Hoshal, Elizabeth de Laittre, Olivier Marre, Michael J. Berry II

End-to-end Stochastic Optimization with Energy-based Model

Lingkai Kong, Jiaming Cui, Yuchen Zhuang, Rui Feng, B. Aditya Prakash

Mingling Foresight with Imagination: Model-Based Cooperative Multi-Agent Reinforcement Learning

Zhiwei Xu, Dapeng Li, Bin Zhang, Yuan Zhan, Yunpeng Baiia

SKFlow: Learning Optical Flow with Super Kernels

SHANGKUN SUN, Yuanqi Chen, Yu Zhu, Guodong Guo, Ge Li

On the difficulty of learning chaotic dynamics with RNNs

Jonas Mikhaeil, Zahra Monfared, Daniel Durstewitz

Improving Self-Supervised Learning by Characterizing Idealized Representations

Yann Dubois, Stefano Ermon, Tatsunori B Hashimoto, Percy Liang

Fairness Transferability Subject to Bounded Distribution Shift

Yatong Chen, Reilly Raab, Jialu Wang, Yang Liu

On the Spectral Bias of Convolutional Neural Tangent and Gaussian Process Kernels

Amnon Geifman, Meirav Galun, David Jacobs, Basri Ronen

AnimeSR: Learning Real-World Super-Resolution Models for Animation Videos

Yanze Wu, Xintao Wang, Gen Li, Ying Shan

Are AlphaZero-like Agents Robust to Adversarial Perturbations?

Li-Cheng Lan, Huan Zhang, Ti-Rong Wu, Meng-Yu Tsai, I-Chen Wu

Brownian Noise Reduction: Maximizing Privacy Subject to Accuracy Constraints

Justin Whitehouse, Aaditya Ramdas, Steven Z. Wu, Ryan M Rogers

Nest Your Adaptive Algorithm for Parameter-Agnostic Nonconvex Minimax Optimization

Junchi Yang, Xiang Li, Niao He

Deep Learning Methods for Proximal Inference via Maximum Moment Restriction

Benjamin Kompa, David Bellamy, Tom Kolokotrones, james m robins, Andrew Beam

Models Out of Line: A Fourier Lens on Distribution Shift Robustness

Sara Fridovich-Keil, Brian Bartoldson, James Diffenderfer, Bhavya Kailkhura, Timo Bremer

Transcormer: Transformer for Sentence Scoring with Sliding Language Modeling

Kaitao Song, Yichong Leng, Xu Tan, Yicheng Zou, Tao Qin

Instance-Based Uncertainty Estimation for Gradient-Boosted Regression Trees

Jonathan Brophy, Daniel Lowd

Bayesian Persuasion for Algorithmic Recourse

Keegan Harris, Valerie Chen, Joon Kim, Ameet Talwalkar, Hoda Heidari

SeqPATE: Differentially Private Text Generation via Knowledge Distillation

Zhiliang Tian, Yingxiu Zhao, Ziyue Huang, Yu-Xiang Wang, Nevin L. Zhang

Class-Dependent Label-Noise Learning with Cycle-Consistency Regularization

De Cheng, Yixiong Ning, Nannan Wang, Xinbo Gao, Heng Yang

Hierarchical Lattice Layer for Partially Monotone Neural Networks

Hiroki Yanagisawa, Kohei Miyaguchi, Takayuki Katsuki

Recurrent Memory Transformer

Aydar Bulatov, Yury Kuratov, Mikhail Burtsev

Provably Feedback-Efficient Reinforcement Learning via Active Reward Learning

Dingwen Kong, Lin Yang

Learning from Distributed Users in Contextual Linear Bandits Without Sharing the Context

Osama Hanna, Lin Yang, Christina Fragouli

PolarMix: A General Data Augmentation Technique for LiDAR Point Clouds

Aoran Xiao, Jiaxing Huang, Dayan Guan, Kaiwen Cui, Shijian Lu

LOG: Active Model Adaptation for Label-Efficient OOD Generalization

Jie-Jing Shao, Lan-Zhe Guo, Xiao-wen Yang, Yu-feng Li

Learning in Congestion Games with Bandit Feedback

Qiwen Cui, Zhihan Xiong, Maryam Fazel, Simon S Du

Momentum Aggregation for Private Non-convex ERM

Hoang Tran, Ashok Cutkosky

On Non-Linear operators for Geometric Deep Learning

Grégoire Sergeant-Perthuis, Jakob Maier, Joan Bruna, Edouard Oyallon

GenerSpeech: Towards Style Transfer for Generalizable Out-Of-Domain Text-to-Speech

Rongjie Huang, Yi Ren, Jinglin Liu, Chenye Cui, Zhou Zhao

Learning Distributions Generated by Single-Layer ReLU Networks in the Presence of Arbitrary Outliers

Saikiran Bulusu, Geethu Joseph, M. Cenk Gursoy, Pramod Varshney

Generic bounds on the approximation error for physics-informed (and) operator learning

Tim De Ryck, Siddhartha Mishra

Deep Multi-Modal Structural Equations For Causal Effect Estimation With Unstructured Proxies

Shachi Deshpande, Kaiwen Wang, Dhruv Sreenivas, Zheng Li, Volodymyr Kuleshov

Towards Practical Control of Singular Values of Convolutional Layers

Alexandra Senderovich, Ekaterina Bulatova, Anton Obukhov, Maxim Rakhuba

Causal Discovery in Heterogeneous Environments Under the Sparse Mechanism Shift Hypothesis

Ronan Perry, Julius von Kügelgen, Bernhard Schölkopf

Understanding the Evolution of Linear Regions in Deep Reinforcement Learning

Setareh Cohan, Nam Hee Kim, David Rolnick, Michiel van de Panne

Posterior and Computational Uncertainty in Gaussian Processes

Jonathan Wenger, Geoff Pleiss, Marvin Pförtner, Philipp Hennig, John P. Cunningham

Stochastic Second-Order Methods Improve Best-Known Sample Complexity of SGD for Gradient-Dominated Functions

Saeed Masiha, Saber Salehkaleybar, Niao He, Negar Kiyavash, Patrick Thiran

Phase transitions in when feedback is useful

Lokesh Boominathan, Xaq Pitkow

Bivariate Causal Discovery for Categorical Data via Classification with Optimal Label Permutation

Yang Ni

Diverse Weight Averaging for Out-of-Distribution Generalization

Alexandre Rame, Matthieu Kirchmeyer, Thibaud Rahier, Alain Rakotomamonjy, Patrick Gallinari

Rethinking and Scaling Up Graph Contrastive Learning: An Extremely Efficient Approach with Group Discrimination

YIZHEN ZHENG, Shirui Pan, Vincent CS Lee, Yu Zheng, Philip S Yu

The Neural Covariance SDE: Shaped Infinite Depth-and-Width Networks at Initialization

Mufan Li, Mihai Nica, Dan Roy

Improved Imaging by Invex Regularizers with Global Optima Guarantees

Samuel Pinilla, Tingting Mu, Neil Bourne, Jeyan Thiyagalingam

Can Push-forward Generative Models Fit Multimodal Distributions?

Antoine Salmona, Valentin De Bortoli, Julie Delon, Agnes Desolneux

On Convergence of FedProx: Local Dissimilarity Invariant Bounds, Non-smoothness and Beyond

Xiaotong Yuan, Ping Li

Optimistic Posterior Sampling for Reinforcement Learning with Few Samples and Tight Guarantees

Daniil Tiapkin, Denis Belomestny, Daniele Calandriello, Eric Moulines, Rémi Munos

Convergence beyond the over-parameterized regime using Rayleigh quotients

David A. R. Robin, Kevin Scaman, marc lelarge

Hardness of Noise-Free Learning for Two-Hidden-Layer Neural Networks

Sitan Chen, Aravind Gollakota, Adam Klivans, Raghu Meka

A Probabilistic Graph Coupling View of Dimension Reduction

Hugues Van Assel, Thibault Espinasse, Julien Chiquet, Franck Picard

Symbolic Distillation for Learned TCP Congestion Control

S P Sharan, Wenqing Zheng, Kuo-Feng Hsu, Jiarong Xing, Ang Chen

Temporally-Consistent Survival Analysis

Lucas Maystre, Daniel Russo

Curriculum Reinforcement Learning using Optimal Transport via Gradual Domain Adaptation

Peide Huang, Mengdi Xu, Jiacheng Zhu, Laixi Shi, Fei Fang

Counterfactual Neural Temporal Point Process for Estimating Causal Influence of Misinformation on Social Media

Yizhou Zhang, Defu Cao, Yan Liu

Memory Efficient Continual Learning with Transformers

Beyza Ermis, Giovanni Zappella, Martin Wistuba, Aditya Rawal, Cédric Archambeau

On Deep Generative Models for Approximation and Estimation of Distributions on Manifolds

Biraj Dahal, Alexander Havrilla, Minshuo Chen, Tuo Zhao, Wenjing Liao

Generalization Bounds for Gradient Methods via Discrete and Continuous Prior

Xuanyuan Luo, Bei Luo, Jian Li

Modeling Transitivity and Cyclicity in Directed Graphs via Binary Code Box Embeddings

Dongxu Zhang, Michael Boratko, Cameron Musco, Andrew McCallum

FedAvg with Fine Tuning: Local Updates Lead to Representation Learning

Liam Collins, Hamed Hassani, Aryan Mokhtari, Sanjay Shakkottai

REVIVE: Regional Visual Representation Matters in Knowledge-Based Visual Question Answering

Yuanze Lin, Yujia Xie, Dongdong Chen, Yichong Xu, Chenguang Zhu

BackdoorBench: A Comprehensive Benchmark of Backdoor Learning

Baoyuan Wu, Hongrui Chen, Mingda Zhang, Zihao Zhu, Shaokui Wei

DReS-FL: Dropout-Resilient Secure Federated Learning for Non-IID Clients via Secret Data Sharing

Jiawei Shao, Yuchang Sun, Songze Li, Jun Zhang

A Near-Optimal Primal-Dual Method for Off-Policy Learning in CMDP

Fan Chen, Junyu Zhang, Zaiwen Wen

Temporal Latent Bottleneck: Synthesis of Fast and Slow Processing Mechanisms in Sequence Learning

Aniket Didolkar, Kshitij Gupta, Anirudh Goyal, Nitesh Bharadwaj Gundavarapu, Alex M Lamb

Revisiting Sparse Convolutional Model for Visual Recognition

xili dai, Mingyang Li, Pengyuan Zhai, Shengbang Tong, Xingjian Gao

NS3: Neuro-symbolic Semantic Code Search

Shushan Arakelyan, Anna Hakhverdyan, Miltiadis Allamanis, Luis Garcia, Christophe Hauser

Near-Optimal Private and Scalable k-Clustering

Vincent Cohen-Addad, Alessandro Epasto, Vahab Mirrokni, Shyam Narayanan, Peilin Zhong

A Closer Look at the Adversarial Robustness of Deep Equilibrium Models

Zonghan Yang, Tianyu Pang, Yang Liu

Automatic Differentiation of Programs with Discrete Randomness

Gaurav Arya, Moritz Schauer, Frank Schäfer, Christopher Rackauckas

BEVFusion: A Simple and Robust LiDAR-Camera Fusion Framework

Tingting Liang, Hongwei Xie, Kaicheng Yu, Zhongyu Xia, Zhiwei Lin

Reduced Representation of Deformation Fields for Effective Non-rigid Shape Matching

Ramana Subramanyam Sundararaman, Riccardo Marin, Emanuele Rodolà, Maks Ovsjanikov

Minimax Optimal Algorithms for Fixed-Budget Best Arm Identification

Junpei Komiyama, Taira Tsuchiya, Junya Honda

Decomposed Knowledge Distillation for Class-Incremental Semantic Segmentation

Donghyeon Baek, Youngmin Oh, Junghyup Lee, Bumsub Ham, Sang-Hoon Lee

Learning Tractable Probabilistic Models from Inconsistent Local Estimates

Shasha Jin, Vasundhara Komaragiri, Tahrima Rahman, Vibhav Gogate

HorNet: Efficient High-Order Spatial Interactions with Recursive Gated Convolutions

Yongming Rao, Wenliang Zhao, Yansong Tang, Jie Zhou, Ser Nam Lim

A Unified Diversity Measure for Multiagent Reinforcement Learning

Zongkai Liu, Chao Yu, Yaodong Yang, peng sun, Zifan Wu

Sound and Complete Causal Identification with Latent Variables Given Local Background Knowledge

Tian-Zuo Wang, Tian Qin, Zhi-Hua Zhou

Wild-Time: A Benchmark of in-the-Wild Distribution Shift over Time

Huaxiu Yao, Caroline Choi, Bochuan Cao, Yoonho Lee, Pang Wei W Koh

EcoFormer: Energy-Saving Attention with Linear Complexity

Jing Liu, Zizheng Pan, Haoyu He, Jianfei Cai, Bohan Zhuang

Gold-standard solutions to the Schrödinger equation using deep learning: How much physics do we need?

Leon Gerard, Michael Scherbela, Philipp Marquetand, Philipp Grohs

End-to-end Symbolic Regression with Transformers

Pierre-Alexandre Kamienny, Stéphane d'Ascoli, Guillaume Lample, Francois Charton

GRASP: Navigating Retrosynthetic Planning with Goal-driven Policy

Yemin Yu, Ying Wei, Kun Kuang, Zhengxing Huang, Huaxiu Yao

Toward Robust Spiking Neural Network Against Adversarial Perturbation

Ling Liang, Kaidi Xu, Xing Hu, Lei Deng, Yuan Xie

How Sampling Impacts the Robustness of Stochastic Neural Networks

Sina Däubener, Asja Fischer

Parameter-Efficient Masking Networks

Yue Bai, Huan Wang, Xu Ma, Yitian Zhang, Zhiqiang Tao

MExMI: Pool-based Active Model Extraction Crossover Membership Inference

Yaxin Xiao, Qingqing Ye, Haibo Hu, Huadi Zheng, Chengfang Fang

Near-Isometric Properties of Kronecker-Structured Random Tensor Embeddings

Qijia Jiang

On Leave-One-Out Conditional Mutual Information For Generalization

Mohamad Rida Rammal, Alessandro Achille, Aditya Golatkar, Suhas Diggavi, Stefano Soatto

On Measuring Excess Capacity in Neural Networks

Florian Graf, Sebastian Zeng, Bastian Rieck, Marc Niethammer, Roland Kwitt

MultiGuard: Provably Robust Multi-label Classification against Adversarial Examples

Jinyuan Jia, Wenjie Qu, Neil Gong

Lost in Latent Space: Examining failures of disentangled models at combinatorial generalisation

Milton Montero, Jeffrey Bowers, Rui Ponte Costa, Casimir Ludwig, Gaurav Malhotra

Maximum-Likelihood Inverse Reinforcement Learning with Finite-Time Guarantees

Siliang Zeng, Chenliang Li, Alfredo Garcia, Mingyi Hong