NeurIPS 2022

2,834 papers

FinRL-Meta: Market Environments and Benchmarks for Data-Driven Financial Reinforcement Learning

Xiao-Yang Liu, Ziyi Xia, Jingyang Rui, Jiechao Gao, Hongyang Yang

Reinforcement Learning with Automated Auxiliary Loss Search

Tairan He, Yuge Zhang, Kan Ren, Minghuan Liu, Che Wang

Neural-Symbolic Entangled Framework for Complex Query Answering

Zezhong Xu, Wen Zhang, Peng Ye, Hui Chen, Huajun Chen

Online Decision Mediation

Daniel Jarrett, Alihan Hüyük, Mihaela van der Schaar

Lethal Dose Conjecture on Data Poisoning

Wenxiao Wang, Alexander Levine, Soheil Feizi

Use-Case-Grounded Simulations for Explanation Evaluation

Valerie Chen, Nari Johnson, Nicholay Topin, Gregory Plumb, Ameet Talwalkar

Functional Ensemble Distillation

Coby Penso, Idan Achituve, Ethan Fetaya

Certifying Robust Graph Classification under Orthogonal Gromov-Wasserstein Threats

Hongwei Jin, Zishun Yu, Xinhua Zhang

Iterative Feature Matching: Toward Provable Domain Generalization with Logarithmic Environments

Yining Chen, Elan Rosenfeld, Mark Sellke, Tengyu Ma, Andrej Risteski

Mildly Conservative Q-Learning for Offline Reinforcement Learning

Jiafei Lyu, Xiaoteng Ma, Xiu Li, Zongqing Lu

LDSA: Learning Dynamic Subtask Assignment in Cooperative Multi-Agent Reinforcement Learning

Mingyu Yang, Jian Zhao, Xunhan Hu, Wengang Zhou, Jiangcheng Zhu

An α-regret analysis of Adversarial Bilateral Trade

Yossi Azar, Amos Fiat, Federico Fusco

StrokeRehab: A Benchmark Dataset for Sub-second Action Identification

Aakash Kaku, Kangning Liu, Avinash Parnandi, Haresh Rengaraj Rajamohan, Kannan Venkataramanan

General Cutting Planes for Bound-Propagation-Based Neural Network Verification

Huan Zhang, Shiqi Wang, Kaidi Xu, Linyi Li, Bo Li

Maximizing Revenue under Market Shrinkage and Market Uncertainty

Maria-Florina F Balcan, Siddharth Prasad, Tuomas Sandholm

Where to Pay Attention in Sparse Training for Feature Selection?

Ghada Sokar, Zahra Atashgahi, Mykola Pechenizkiy, Decebal Constantin Mocanu

Learning Robust Dynamics through Variational Sparse Gating

Arnav Kumar Jain, Shivakanth Sujit, Shruti Joshi, Vincent Michalski, Danijar Hafner

PDEBench: An Extensive Benchmark for Scientific Machine Learning

Makoto Takamoto, Timothy Praditia, Raphael Leiteritz, Daniel MacKinlay, Francesco Alesiani

AdaFocal: Calibration-aware Adaptive Focal Loss

Arindam Ghosh, Thomas Schaaf, Matthew Gormley

S$^3$-NeRF: Neural Reflectance Field from Shading and Shadow under a Single Viewpoint

Wenqi Yang, Guanying Chen, Chaofeng Chen, Zhenfang Chen, Kwan-Yee K. Wong

Provable Subspace Identification Under Post-Nonlinear Mixtures

Qi Lyu, Xiao Fu

When does return-conditioned supervised learning work for offline reinforcement learning?

David Brandfonbrener, Alberto Bietti, Jacob Buckman, Romain Laroche, Joan Bruna

Learning to Navigate Wikipedia by Taking Random Walks

Manzil Zaheer, Kenneth Marino, Will Grathwohl, John Schultz, Wendy Shang

Adaptive Data Debiasing through Bounded Exploration

Yifan Yang, Yang Liu, Parinaz Naghizadeh

Multi-Sample Training for Neural Image Compression

Tongda Xu, Yan Wang, Dailan He, Chenjian Gao, Han Gao

Efficient and Effective Augmentation Strategy for Adversarial Training

Sravanti Addepalli, Samyak Jain, Venkatesh Babu R

Cross-Image Context for Single Image Inpainting

Tingliang Feng, Wei Feng, Weiqi Li, Di Lin

Learning in Observable POMDPs, without Computationally Intractable Oracles

Noah Golowich, Ankur Moitra, Dhruv Rohatgi

OccGen: Selection of Real-world Multilingual Parallel Data Balanced in Gender within Occupations

Marta Costa-jussà, Christine Basta, Oriol Domingo, André Rubungo

Riemannian Neural SDE: Learning Stochastic Representations on Manifolds

Sung Woo Park, Hyomin Kim, Kyungjae Lee, Junseok Kwon

TweetNERD - End to End Entity Linking Benchmark for Tweets

Shubhanshu Mishra, Aman Saini, Raheleh Makki, Sneha Mehta, Aria Haghighi

Towards Efficient Post-training Quantization of Pre-trained Language Models

Haoli Bai, Lu Hou, Lifeng Shang, Xin Jiang, Irwin King

Emergent Communication: Generalization and Overfitting in Lewis Games

Mathieu Rita, Corentin Tallec, Paul Michel, Jean-Bastien Grill, Olivier Pietquin

Museformer: Transformer with Fine- and Coarse-Grained Attention for Music Generation

Botao Yu, Peiling Lu, Rui Wang, Wei Hu, Xu Tan

Revisiting Heterophily For Graph Neural Networks

Sitao Luan, Chenqing Hua, Qincheng Lu, Jiaqi Zhu, Mingde Zhao

Okapi: Generalising Better by Making Statistical Matches Match

Myles Bartlett, Sara Romiti, Viktoriia Sharmanska, Novi Quadrianto

Neural Stochastic PDEs: Resolution-Invariant Learning of Continuous Spatiotemporal Dynamics

Cristopher Salvi, Maud Lemercier, Andris Gerasimovics

Decision-Focused Learning without Decision-Making: Learning Locally Optimized Decision Losses

Sanket Shah, Kai Wang, Bryan Wilder, Andrew Perrault, Milind Tambe

Boosting Barely Robust Learners: A New Perspective on Adversarial Robustness

Avrim Blum, Omar Montasser, Greg Shakhnarovich, Hongyang Zhang

Semi-supervised Active Linear Regression

Nived Rajaraman, Fnu Devvrit, Pranjal Awasthi

Predictive Coding beyond Gaussian Distributions

Luca Pinchetti, Tommaso Salvatori, Yordan Yordanov, Beren Millidge, Yuhang Song

Algorithms and Hardness for Learning Linear Thresholds from Label Proportions

Rishi Saket

Controlled Sparsity via Constrained Optimization or: How I Learned to Stop Tuning Penalties and Love Constraints

Jose Gallego-Posada, Juan Ramirez, Akram Erraqabi, Yoshua Bengio, Simon Lacoste-Julien

Counterfactual Fairness with Partially Known Causal Graph

Aoqi Zuo, Susan Wei, Tongliang Liu, Bo Han, Kun Zhang

MABSplit: Faster Forest Training Using Multi-Armed Bandits

Mo Tiwari, Ryan Kang, Jaeyong Lee, Chris Piech, Ilan Shomorony

An Empirical Study on Disentanglement of Negative-free Contrastive Learning

Jinkun Cao, Ruiqian Nai, Qing Yang, jialei huang, Yang Gao

Pre-trained Adversarial Perturbations

Yuanhao Ban, Yinpeng Dong

Benign, Tempered, or Catastrophic: Toward a Refined Taxonomy of Overfitting

Neil Mallinar, James Simon, Amirhesam Abedsoltan, Parthe Pandit, Misha Belkin

Syndicated Bandits: A Framework for Auto Tuning Hyper-parameters in Contextual Bandit Algorithms

QIN DING, Yue Kang, Thomas Chun Man Lee, Cho-jui Hsieh, James Sharpnack

Understanding Hyperdimensional Computing for Parallel Single-Pass Learning

Tao Yu, Yichi Zhang, Zhiru Zhang, Christopher M De Sa

SegNeXt: Rethinking Convolutional Attention Design for Semantic Segmentation

Meng-Hao Guo, Cheng-Ze Lu, Qibin Hou, Zhengning Liu, Ming-Ming Cheng

A Large Scale Search Dataset for Unbiased Learning to Rank

Lixin Zou, Haitao Mao, Xiaokai Chu, Jiliang Tang, Wenwen Ye

Adaptive Sampling for Discovery

Ziping Xu, Eunjae Shim, Ambuj Tewari, Paul Zimmerman

Dataset Distillation via Factorization

Songhua Liu, Kai Wang, Xingyi Yang, Jingwen Ye, Xinchao Wang

Moderate-fitting as a Natural Backdoor Defender for Pre-trained Language Models

Biru Zhu, Yujia Qin, Ganqu Cui, Yangyi Chen, Weilin Zhao

Communication-Efficient Topologies for Decentralized Learning with $O(1)$ Consensus Rate

Zhuoqing Song, Weijian Li, Kexin Jin, Lei Shi, Ming Yan

Improved Regret Analysis for Variance-Adaptive Linear Bandits and Horizon-Free Linear Mixture MDPs

Yeoneung Kim, Insoon Yang, Kwang-Sung Jun

DOPE: Doubly Optimistic and Pessimistic Exploration for Safe Reinforcement Learning

Archana Bura, Aria HasanzadeZonuzy, Dileep Kalathil, Srinivas Shakkottai, Jean-Francois Chamberland

Accelerated Training of Physics-Informed Neural Networks (PINNs) using Meshless Discretizations

Ramansh Sharma, Varun Shankar

Efficient Multi-agent Communication via Self-supervised Information Aggregation

Cong Guan, Feng Chen, Lei Yuan, Chenghe Wang, Hao Yin

UniCLIP: Unified Framework for Contrastive Language-Image Pre-training

Janghyeon Lee, Jongsuk Kim, Hyounguk Shon, Bumsoo Kim, Seung Hwan Kim

Batch Multi-Fidelity Active Learning with Budget Constraints

Shibo Li, Jeff M Phillips, Xin Yu, Robert Kirby, Shandian Zhe

Global Optimal K-Medoids Clustering of One Million Samples

Jiayang Ren, Kaixun Hua, Yankai Cao

Neural Surface Reconstruction of Dynamic Scenes with Monocular RGB-D Camera

Hongrui Cai, Wanquan Feng, Xuetao Feng, Yan Wang, Juyong Zhang

Why Do Artificially Generated Data Help Adversarial Robustness

Yue Xing, Qifan Song, Guang Cheng

Learning Best Combination for Efficient N:M Sparsity

Yuxin Zhang, Mingbao Lin, ZhiHang Lin, Yiting Luo, Ke Li

Learning Probabilistic Models from Generator Latent Spaces with Hat EBM

Mitch Hill, Erik Nijkamp, Jonathan Mitchell, Bo Pang, Song-chun Zhu

Environment Diversification with Multi-head Neural Network for Invariant Learning

Bo-Wei Huang, Keng-Te Liao, Chang-Sheng Kao, Shou-De Lin

Sparsity in Continuous-Depth Neural Networks

Hananeh Aliee, Till Richter, Mikhail Solonin, Ignacio Ibarra, Fabian J. Theis

Density-driven Regularization for Out-of-distribution Detection

Wenjian Huang, Hao Wang, Jiahao Xia, Chengyan Wang, Jianguo Zhang

Causal Discovery in Linear Latent Variable Models Subject to Measurement Error

Yuqin Yang, AmirEmad Ghassami, Mohamed Nafea, Negar Kiyavash, Kun Zhang

Trimmed Maximum Likelihood Estimation for Robust Generalized Linear Model

Pranjal Awasthi, Abhimanyu Das, Weihao Kong, Rajat Sen

Differentially Private Covariance Revisited

Wei Dong, Yuting Liang, Ke Yi

Queue Up Your Regrets: Achieving the Dynamic Capacity Region of Multiplayer Bandits

Ilai Bistritz, Nicholas Bambos

Mask Matching Transformer for Few-Shot Segmentation

siyu jiao, Gengwei Zhang, Shant Navasardyan, Ling Chen, Yao Zhao

DC-BENCH: Dataset Condensation Benchmark

Justin CUI, Ruochen Wang, Si Si, Cho-jui Hsieh

On the Frequency-bias of Coordinate-MLPs

Sameera Ramasinghe, Lachlan E. MacDonald, Simon Lucey

Multi-Class H-Consistency Bounds

Pranjal Awasthi, Anqi Mao, Mehryar Mohri, Yutao Zhong

Unsupervised Learning of Equivariant Structure from Sequences

Takeru Miyato, Masanori Koyama, Kenji Fukumizu

On Divergence Measures for Bayesian Pseudocoresets

Balhae Kim, Jungwon Choi, Seanie Lee, Yoonho Lee, Jung-Woo Ha

Early Stage Convergence and Global Convergence of Training Mildly Parameterized Neural Networks

Mingze Wang, Chao Ma

Learning to Configure Computer Networks with Neural Algorithmic Reasoning

Luca Beurer-Kellner, Martin Vechev, Laurent Vanbever, Petar Veličković

BR-SNIS: Bias Reduced Self-Normalized Importance Sampling

Gabriel Cardoso, Sergey Samsonov, Achille Thin, Eric Moulines, Jimmy Olsson

Differentially Private Learning Needs Hidden State (Or Much Faster Convergence)

Jiayuan Ye, Reza Shokri

Between Stochastic and Adversarial Online Convex Optimization: Improved Regret Bounds via Smoothness

Sarah Sachs, Hedi Hadiji, Tim van Erven, Cristóbal Guzmán

Tiered Reinforcement Learning: Pessimism in the Face of Uncertainty and Constant Regret

Jiawei Huang, Li Zhao, Tao Qin, Wei Chen, Nan Jiang

VLMbench: A Compositional Benchmark for Vision-and-Language Manipulation

Kaizhi Zheng, Xiaotong Chen, Odest Chadwicke Jenkins, Xin Wang

ComENet: Towards Complete and Efficient Message Passing for 3D Molecular Graphs

Limei Wang, Yi Liu, Yuchao Lin, Haoran Liu, Shuiwang Ji

Shadow Knowledge Distillation: Bridging Offline and Online Knowledge Transfer

Lujun Li, ZHE JIN

Decoupled Self-supervised Learning for Graphs

Teng Xiao, Zhengyu Chen, Zhimeng Guo, Zeyang Zhuang, Suhang Wang

Efficient Knowledge Distillation from Model Checkpoints

Chaofei Wang, Qisen Yang, Rui Huang, Shiji Song, Gao Huang

Off-Policy Evaluation for Episodic Partially Observable Markov Decision Processes under Non-Parametric Models

Rui Miao, Zhengling Qi, Xiaoke Zhang

Provably Efficient Reinforcement Learning in Partially Observable Dynamical Systems

Masatoshi Uehara, Ayush Sekhari, Jason Lee, Nathan Kallus, Wen Sun

Parallel Tempering With a Variational Reference

Nikola Surjanovic, Saifuddin Syed, Alexandre Bouchard-côté, Trevor Campbell

Identifiability and generalizability from multiple experts in Inverse Reinforcement Learning

Paul Rolland, Luca Viano, Norman Schürhoff, Boris Nikolov, Volkan Cevher

Markovian Interference in Experiments

Vivek Farias, Andrew Li, Tianyi Peng, Andrew Zheng

Generalizing Consistent Multi-Class Classification with Rejection to be Compatible with Arbitrary Losses

Yuzhou Cao, Tianchi Cai, Lei Feng, Lihong Gu, Jinjie GU

Why do tree-based models still outperform deep learning on typical tabular data?

Leo Grinsztajn, Edouard Oyallon, Gael Varoquaux

Robust Binary Models by Pruning Randomly-initialized Networks

Chen Liu, Ziqi Zhao, Sabine Süsstrunk, Mathieu Salzmann

Wavelet Score-Based Generative Modeling

Florentin Guth, Simon Coste, Valentin De Bortoli, Stephane Mallat