NeurIPS 2022

2,834 papers

Cooperative Distribution Alignment via JSD Upper Bound

Wonwoong Cho, ZIYU GONG, David I Inouye

A Coupled Design of Exploiting Record Similarity for Practical Vertical Federated Learning

Zhaomin Wu, Qinbin Li, Bingsheng He

Alleviating the Sample Selection Bias in Few-shot Learning by Removing Projection to the Centroid

Jing Xu, Xu Luo, Xinglin Pan, Yanan Li, Wenjie Pei

Laplacian Autoencoders for Learning Stochastic Representations

Marco Miani, Frederik Warburg, Pablo Moreno-Muñoz, Nicki Skafte, Søren Hauberg

Neuron with Steady Response Leads to Better Generalization

Qiang Fu, Lun Du, Haitao Mao, Xu Chen, Wei Fang

Ordered Subgraph Aggregation Networks

Chendi Qian, Gaurav Rattan, Floris Geerts, Mathias Niepert, Christopher Morris

Generalizing Bayesian Optimization with Decision-theoretic Entropies

Willie Neiswanger, Lantao Yu, Shengjia Zhao, Chenlin Meng, Stefano Ermon

CAESAR: An Embodied Simulator for Generating Multimodal Referring Expression Datasets

Md Mofijul Islam, Reza Mirzaiee, Alexi Gladstone, Haley Green, Tariq Iqbal

Discrete-Convex-Analysis-Based Framework for Warm-Starting Algorithms with Predictions

Shinsaku Sakaue, Taihei Oki

Pessimism for Offline Linear Contextual Bandits using ℓ_p Confidence Sets

Gene Li, Cong Ma, Nati Srebro

On the Statistical Efficiency of Reward-Free Exploration in Non-Linear RL

Jinglin Chen, Aditya Modi, Akshay Krishnamurthy, Nan Jiang, Alekh Agarwal

Task-level Differentially Private Meta Learning

Xinyu Zhou, Raef Bassily

Diversity vs. Recognizability: Human-like generalization in one-shot generative models

Victor Boutin, Lakshya Singhal, Xavier Thomas, Thomas Serre

Gradient Methods Provably Converge to Non-Robust Networks

Gal Vardi, Gilad Yehudai, Ohad Shamir

Losses Can Be Blessings: Routing Self-Supervised Speech Representations Towards Efficient Multilingual and Multitask Speech Processing

Yonggan Fu, Yang Zhang, Kaizhi Qian, Zhifan Ye, Zhongzhi Yu

Hao Lu, Wenze Liu, Zixuan Ye, Hongtao Fu, Yuliang Liu

Bayesian inference via sparse Hamiltonian flows

Naitong Chen, Zuheng Xu, Trevor Campbell

Structured Energy Network As a Loss

Jay Yoon Lee, Dhruvesh Patel, Purujit Goyal, Wenlong Zhao, Zhiyang Xu

A Fourier Approach to Mixture Learning

Mingda Qiao, Guru Guruganesh, Ankit Rawat, Kumar Avinava Dubey, Manzil Zaheer

Biological Learning of Irreducible Representations of Commuting Transformations

Alexander Genkin, David Lipshutz, Siavash Golkar, Tiberiu Tesileanu, Dmitri B. Chklovskii

MetaTeacher: Coordinating Multi-Model Domain Adaptation for Medical Image Classification

Zhenbin Wang, Mao Ye, Xiatian Zhu, Liuhan Peng, Liang Tian

Multiclass Learnability Beyond the PAC Framework: Universal Rates and Partial Concept Classes

Alkis Kalavasis, Grigoris Velegkas, Amin Karbasi

Symplectic Spectrum Gaussian Processes: Learning Hamiltonians from Noisy and Sparse Data

Yusuke Tanaka, Tomoharu Iwata, Naonori Ueda

Invariant and Transportable Representations for Anti-Causal Domain Shifts

Yibo Jiang, Victor Veitch

Dynamic Learning in Large Matching Markets

Anand Kalvit, Assaf J. Zeevi

Boosting Out-of-distribution Detection with Typical Features

Yao Zhu, YueFeng Chen, Chuanlong Xie, Xiaodan Li, Rong Zhang

WebShop: Towards Scalable Real-World Web Interaction with Grounded Language Agents

Shunyu Yao, Howard Chen, John Yang, Karthik Narasimhan

SCONE: Surface Coverage Optimization in Unknown Environments by Volumetric Integration

Antoine Guedon, Pascal Monasse, Vincent Lepetit

Online Training Through Time for Spiking Neural Networks

Mingqing Xiao, Qingyan Meng, Zongpeng Zhang, Di He, Zhouchen Lin

Model-Based Imitation Learning for Urban Driving

Anthony Hu, Gianluca Corrado, Nicolas Griffiths, Zachary Murez, Corina Gurau

Additive MIL: Intrinsically Interpretable Multiple Instance Learning for Pathology

Syed Ashar Javed, Dinkar Juyal, Harshith Padigela, Amaro Taylor-Weiner, Limin Yu

Self-Aware Personalized Federated Learning

Huili Chen, Jie Ding, Shuang Wu, Anit Kumar Sahu, Salman Avestimehr

SPD: Synergy Pattern Diversifying Oriented Unsupervised Multi-agent Reinforcement Learning

Yuhang Jiang, Jianzhun Shao, Shuncheng He, Hongchang Zhang, Xiangyang Ji

Evaluated CMI Bounds for Meta Learning: Tightness and Expressiveness

Fredrik Hellström, Giuseppe Durisi

Graph Neural Networks are Dynamic Programmers

Andrew J Dudzik, Petar Veličković

Finding Optimal Arms in Non-stochastic Combinatorial Bandits with Semi-bandit Feedback and Finite Budget

Jasmin Brandt, Viktor Bengs, Björn Haddenhorst, Eyke Hüllermeier

Biologically plausible solutions for spiking networks with efficient coding

Veronika Koren, Stefano Panzeri

Wavelet Feature Maps Compression for Image-to-Image CNNs

Shahaf E. Finder, Yair Zohav, Maor Ashkenazi, Eran Treister

Exploiting the Relationship Between Kendall's Rank Correlation and Cosine Similarity for Attribution Protection

Fan Wang, Adams Wai Kin Kong

On the Robustness of Deep Clustering Models: Adversarial Attacks and Defenses

Anshuman Chhabra, Ashwin Sekhari, Prasant Mohapatra

Data Augmentation for Compositional Data: Advancing Predictive Models of the Microbiome

Elliott Gordon-Rodriguez, Thomas Quinn, John P. Cunningham

MVP-N: A Dataset and Benchmark for Real-World Multi-View Object Classification

REN WANG, Jiayue Wang, Tae Sung Kim, JINSUNG KIM, Hyuk-Jae Lee

Language Conditioned Spatial Relation Reasoning for 3D Object Grounding

Shizhe Chen, Pierre-Louis Guhur, Makarand Tapaswi, Cordelia Schmid, Ivan Laptev

Constrained Langevin Algorithms with L-mixing External Random Variables

Yuping Zheng, Andrew Lamperski

AutoST: Towards the Universal Modeling of Spatio-temporal Sequences

Jianxin Li, SHUAI ZHANG, Hui Xiong, Haoyi Zhou

Planning to the Information Horizon of BAMDPs via Epistemic State Abstraction

Dilip Arumugam, Satinder P. Singh

I2Q: A Fully Decentralized Q-Learning Algorithm

Jiechuan Jiang, Zongqing Lu

CLOOB: Modern Hopfield Networks with InfoLOOB Outperform CLIP

Andreas Fürst, Elisabeth Rumetshofer, Johannes Lehner, Viet T. Tran, Fei Tang

SIREN: Shaping Representations for Detecting Out-of-Distribution Objects

Xuefeng Du, Gabriel Gozum, Yifei Ming, Yixuan Li

Pyramid Attention For Source Code Summarization

Lei Chai, Ming Li

Contrastive Graph Structure Learning via Information Bottleneck for Recommendation

Chunyu Wei, Jian Liang, Di Liu, Fei Wang

Spectrum Random Masking for Generalization in Image-based Reinforcement Learning

Yangru Huang, Peixi Peng, Yifan Zhao, Guangyao Chen, Yonghong Tian

Adaptively Exploiting d-Separators with Causal Bandits

Blair Bilodeau, Linbo Wang, Dan Roy

SparCL: Sparse Continual Learning on the Edge

Zifeng Wang, Zheng Zhan, Yifan Gong, Geng Yuan, Wei Niu

Chroma-VAE: Mitigating Shortcut Learning with Generative Classifiers

Wanqian Yang, Polina Kirichenko, Micah Goldblum, Andrew G Wilson

Optimal and Adaptive Monteiro-Svaiter Acceleration

Yair Carmon, Danielle Hausler, Arun Jambulapati, Yujia Jin, Aaron Sidford

Non-Stationary Bandits under Recharging Payoffs: Improved Planning with Sublinear Regret

Orestis Papadigenopoulos, Constantine Caramanis, Sanjay Shakkottai

Versatile Multi-stage Graph Neural Network for Circuit Representation

Shuwen Yang, Zhihao Yang, Dong Li, Yingxueff Zhang, Zhanguang Zhang

Instability and Local Minima in GAN Training with Kernel Discriminators

Evan Becker, Parthe Pandit, Sundeep Rangan, Alyson K. Fletcher

A Unified Hard-Constraint Framework for Solving Geometrically Complex PDEs

Songming Liu, Hao Zhongkai, Chengyang Ying, Hang Su, Jun Zhu

Algorithms with Prediction Portfolios

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

OOD Link Prediction Generalization Capabilities of Message-Passing GNNs in Larger Test Graphs

Yangze Zhou, Gitta Kutyniok, Bruno Ribeiro

Smooth Fictitious Play in Stochastic Games with Perturbed Payoffs and Unknown Transitions

Lucas Baudin, Rida Laraki

End-to-end Algorithm Synthesis with Recurrent Networks: Extrapolation without Overthinking

Arpit Bansal, Avi Schwarzschild, Eitan Borgnia, Zeyad Emam, Furong Huang

Uncertainty-Aware Reinforcement Learning for Risk-Sensitive Player Evaluation in Sports Game

Guiliang Liu, Yudong Luo, Oliver Schulte, Pascal Poupart

Score-based Generative Modeling Secretly Minimizes the Wasserstein Distance

Dohyun Kwon, Ying Fan, Kangwook Lee

Continuous MDP Homomorphisms and Homomorphic Policy Gradient

Sahand Rezaei-Shoshtari, Rosie Zhao, Prakash Panangaden, David Meger, Doina Precup

Experimental Design for Linear Functionals in Reproducing Kernel Hilbert Spaces

Mojmir Mutny, Andreas Krause

TaSIL: Taylor Series Imitation Learning

Daniel Pfrommer, Thomas Zhang, Stephen Tu, Nikolai Matni

Multi-agent Dynamic Algorithm Configuration

Ke Xue, Jiacheng Xu, Lei Yuan, Miqing Li, Chao Qian

Outsourcing Training without Uploading Data via Efficient Collaborative Open-Source Sampling

Junyuan Hong, Lingjuan Lyu, Jiayu Zhou, Michael Spranger

Weisfeiler and Leman Go Walking: Random Walk Kernels Revisited

Nils M. Kriege

Gradient flow dynamics of shallow ReLU networks for square loss and orthogonal inputs

Etienne Boursier, Loucas Pillaud-Vivien, Nicolas Flammarion

Large-Scale Retrieval for Reinforcement Learning

Peter Humphreys, Arthur Guez, Olivier Tieleman, Laurent Sifre, Theophane Weber

Pay attention to your loss : understanding misconceptions about Lipschitz neural networks

Louis Béthune, Thibaut Boissin, Mathieu Serrurier, Franck Mamalet, Corentin Friedrich

Causality-driven Hierarchical Structure Discovery for Reinforcement Learning

shaohui peng, Xing Hu, Rui Zhang, Ke Tang, Jiaming Guo

Low-rank lottery tickets: finding efficient low-rank neural networks via matrix differential equations

Steffen Schotthöfer, Emanuele Zangrando, Jonas Kusch, Gianluca Ceruti, Francesco Tudisco

Interaction Modeling with Multiplex Attention

Fan-Yun Sun, Isaac Kauvar, Ruohan Zhang, Jiachen Li, Mykel J Kochenderfer

Towards Reliable Simulation-Based Inference with Balanced Neural Ratio Estimation

Arnaud Delaunoy, Joeri Hermans, François Rozet, Antoine Wehenkel, Gilles Louppe

Simultaneous Missing Value Imputation and Structure Learning with Groups

Pablo Morales-Alvarez, Wenbo Gong, Angus Lamb, Simon Woodhead, Simon Peyton Jones

Green Hierarchical Vision Transformer for Masked Image Modeling

Lang Huang, Shan You, Mingkai Zheng, Fei Wang, Chen Qian

A Projection-free Algorithm for Constrained Stochastic Multi-level Composition Optimization

Tesi Xiao, Krishnakumar Balasubramanian, Saeed Ghadimi

Efficient Frameworks for Generalized Low-Rank Matrix Bandit Problems

Yue Kang, Cho-jui Hsieh, Thomas Chun Man Lee

Learn to Match with No Regret: Reinforcement Learning in Markov Matching Markets

Yifei Min, Tianhao Wang, Ruitu Xu, Zhaoran Wang, Michael I. Jordan

Faster Deep Reinforcement Learning with Slower Online Network

Kavosh Asadi, Rasool Fakoor, Omer Gottesman, Taesup Kim, Michael L. Littman

GALOIS: Boosting Deep Reinforcement Learning via Generalizable Logic Synthesis

Yushi Cao, Zhiming Li, Tianpei Yang, Hao Zhang, YAN ZHENG

AutoMS: Automatic Model Selection for Novelty Detection with Error Rate Control

Yifan Zhang, Haiyan Jiang, Haojie Ren, Changliang Zou, Dejing Dou

Generative Neural Articulated Radiance Fields

Alexander Bergman, Petr Kellnhofer, Wang Yifan, Eric Chan, David Lindell

Understanding Benign Overfitting in Gradient-Based Meta Learning

Lisha Chen, Songtao Lu, Tianyi Chen

Neural Temporal Walks: Motif-Aware Representation Learning on Continuous-Time Dynamic Graphs

Ming Jin, Yuan-Fang Li, Shirui Pan

Low-Rank Modular Reinforcement Learning via Muscle Synergy

Heng Dong, Tonghan Wang, Jiayuan Liu, Chongjie Zhang

Improving Barely Supervised Learning by Discriminating Unlabeled Samples with Super-Class

Guan Gui, Zhen Zhao, Lei Qi, Luping Zhou, Lei Wang

Lipschitz Bandits with Batched Feedback

Yasong Feng, zengfeng Huang, Tianyu Wang

Bridging the Gap from Asymmetry Tricks to Decorrelation Principles in Non-contrastive Self-supervised Learning

Kang-Jun Liu, Masanori Suganuma, Takayuki Okatani

GStarX: Explaining Graph Neural Networks with Structure-Aware Cooperative Games

Shichang Zhang, Yozen Liu, Neil Shah, Yizhou Sun

ELIAS: End-to-End Learning to Index and Search in Large Output Spaces

Nilesh Gupta, Patrick Chen, Hsiang-Fu Yu, Cho-jui Hsieh, Inderjit S Dhillon

Trust Region Policy Optimization with Optimal Transport Discrepancies: Duality and Algorithm for Continuous Actions

Antonio Terpin, Nicolas Lanzetti, Batuhan Yardim, Florian Dorfler, Giorgia Ramponi

Communication Efficient Distributed Learning for Kernelized Contextual Bandits

Chuanhao Li, Huazheng Wang, Mengdi Wang, Hongning Wang

Robust Imitation of a Few Demonstrations with a Backwards Model

Jung Yeon Park, Lawson Wong

Graph Neural Networks with Adaptive Readouts

David Buterez, Jon Paul Janet, Steven J Kiddle, Dino Oglic, Pietro Lió