NeurIPS 2022

2,834 papers

The Impact of Task Underspecification in Evaluating Deep Reinforcement Learning

Vindula Jayawardana, Catherine Tang, Sirui Li, Dajiang Suo, Cathy Wu

Optimal Scaling for Locally Balanced Proposals in Discrete Spaces

Haoran Sun, Hanjun Dai, Dale Schuurmans

RORL: Robust Offline Reinforcement Learning via Conservative Smoothing

Rui Yang, Chenjia Bai, Xiaoteng Ma, Zhaoran Wang, Chongjie Zhang

Distinguishing discrete and continuous behavioral variability using warped autoregressive HMMs

Julia Costacurta, Lea Duncker, Blue Sheffer, Winthrop Gillis, Caleb Weinreb

DISCO: Adversarial Defense with Local Implicit Functions

Chih-Hui Ho, Nuno Vasconcelos

Hand-Object Interaction Image Generation

Hezhen Hu, Weilun Wang, Wengang Zhou, Houqiang Li

NeuroSchedule: A Novel Effective GNN-based Scheduling Method for High-level Synthesis

Jun Zeng, Mingyang Kou, Hailong Yao

Context-Based Dynamic Pricing with Partially Linear Demand Model

Jinzhi Bu, David Simchi-Levi, Chonghuan Wang

Learning State-Aware Visual Representations from Audible Interactions

Himangi Mittal, Pedro Morgado, Unnat Jain, Abhinav Gupta

Predictive Querying for Autoregressive Neural Sequence Models

Alex Boyd, Samuel Showalter, Stephan Mandt, Padhraic Smyth

Understanding the Eluder Dimension

Gene Li, Pritish Kamath, Dylan J Foster, Nati Srebro

Flamingo: a Visual Language Model for Few-Shot Learning

Jean-Baptiste Alayrac, Jeff Donahue, Pauline Luc, Antoine Miech, Iain Barr

ConfLab: A Data Collection Concept, Dataset, and Benchmark for Machine Analysis of Free-Standing Social Interactions in the Wild

Chirag Raman, Jose Vargas Quiros, Stephanie Tan, Ashraful Islam, Ekin Gedik

BinauralGrad: A Two-Stage Conditional Diffusion Probabilistic Model for Binaural Audio Synthesis

Yichong Leng, Zehua Chen, Junliang Guo, Haohe Liu, Jiawei Chen

Task-Free Continual Learning via Online Discrepancy Distance Learning

Fei Ye, Adrian G. Bors

Data-IQ: Characterizing subgroups with heterogeneous outcomes in tabular data

Nabeel Seedat, Jonathan Crabbe, Ioana Bica, Mihaela van der Schaar

A Characterization of Semi-Supervised Adversarially Robust PAC Learnability

Idan Attias, Steve Hanneke, Yishay Mansour

Tractable Optimality in Episodic Latent MABs

Jeongyeol Kwon, Yonathan Efroni, Constantine Caramanis, Shie Mannor

Adversarial Training with Complementary Labels: On the Benefit of Gradually Informative Attacks

Jianan Zhou, Jianing Zhu, Jingfeng ZHANG, Tongliang Liu, Gang Niu

On Translation and Reconstruction Guarantees of the Cycle-Consistent Generative Adversarial Networks

Anish Chakrabarty, Swagatam Das

Denoising Diffusion Restoration Models

Bahjat Kawar, Michael Elad, Stefano Ermon, Jiaming Song

SageMix: Saliency-Guided Mixup for Point Clouds

Sanghyeok Lee, Minkyu Jeon, Injae Kim, Yunyang Xiong, Hyunwoo J Kim

Mesoscopic modeling of hidden spiking neurons

Shuqi Wang, Valentin Schmutz, Guillaume Bellec, Wulfram Gerstner

Generalization Properties of NAS under Activation and Skip Connection Search

Zhenyu Zhu, Fanghui Liu, Grigorios Chrysos, Volkan Cevher

Thinking Outside the Ball: Optimal Learning with Gradient Descent for Generalized Linear Stochastic Convex Optimization

Idan Amir, Roi Livni, Nati Srebro

Adaptive Stochastic Variance Reduction for Non-convex Finite-Sum Minimization

Ali Kavis, Stratis Skoulakis, Kimon Antonakopoulos, Leello Tadesse Dadi, Volkan Cevher

ElasticMVS: Learning elastic part representation for self-supervised multi-view stereopsis

Jinzhi Zhang, Ruofan Tang, Zheng Cao, Jing Xiao, Ruqi Huang

Inception Transformer

Chenyang Si, Weihao Yu, Pan Zhou, Yichen Zhou, Xinchao Wang

Generalization for multiclass classification with overparameterized linear models

Vignesh Subramanian, Rahul Arya, Anant Sahai

AirfRANS: High Fidelity Computational Fluid Dynamics Dataset for Approximating Reynolds-Averaged Navier–Stokes Solutions

Florent Bonnet, Jocelyn Mazari, Paola Cinnella, Patrick Gallinari

Generalization Error Bounds on Deep Learning with Markov Datasets

Lan V. Truong

Sharpness-Aware Training for Free

JIAWEI DU, Daquan Zhou, Jiashi Feng, Vincent Tan, Joey Tianyi Zhou

Meta-Auto-Decoder for Solving Parametric Partial Differential Equations

Xiang Huang, Zhanhong Ye, Hongsheng Liu, Shi Ji, Zidong Wang

MoVQ: Modulating Quantized Vectors for High-Fidelity Image Generation

Chuanxia Zheng, Tung-Long Vuong, Jianfei Cai, Dinh Phung

Adaptive Oracle-Efficient Online Learning

Guanghui Wang, Zihao Hu, Vidya Muthukumar, Jacob D. Abernethy

Addressing Leakage in Concept Bottleneck Models

Marton Havasi, Sonali Parbhoo, Finale Doshi-velez

MCVD - Masked Conditional Video Diffusion for Prediction, Generation, and Interpolation

Vikram Voleti, Alexia Jolicoeur-Martineau, Chris Pal

Efficient and Stable Fully Dynamic Facility Location

Sayan Bhattacharya, Silvio Lattanzi, Nikos Parotsidis

Video-based Human-Object Interaction Detection from Tubelet Tokens

Danyang Tu, Wei Sun, Xiongkuo Min, Guangtao Zhai, Wei Shen

Sample-Then-Optimize Batch Neural Thompson Sampling

Zhongxiang Dai, YAO SHU, Bryan Kian Hsiang Low, Patrick Jaillet

Decomposing NeRF for Editing via Feature Field Distillation

Sosuke Kobayashi, Eiichi Matsumoto, Vincent Sitzmann

A Dataset for Efforts Towards Achieving the Sustainable Development Goal of Safe Working Environments

Eirik Lund Flogard, Ole Jakob Mengshoel

MaskTune: Mitigating Spurious Correlations by Forcing to Explore

Saeid Asgari, Aliasghar Khani, Fereshte Khani, Ali Gholami, Linh Tran

Adapting Self-Supervised Vision Transformers by Probing Attention-Conditioned Masking Consistency

Viraj Prabhu, Sriram Yenamandra, Aaditya Singh, Judy Hoffman

Constrained Stochastic Nonconvex Optimization with State-dependent Markov Data

Abhishek Roy, Krishnakumar Balasubramanian, Saeed Ghadimi

Phase diagram of Stochastic Gradient Descent in high-dimensional two-layer neural networks

Rodrigo Veiga, Ludovic Stephan, Bruno Loureiro, Florent Krzakala, Lenka Zdeborová

Mismatched No More: Joint Model-Policy Optimization for Model-Based RL

Benjamin Eysenbach, Alexander Khazatsky, Sergey Levine, Ruslan Salakhutdinov

Physics-Embedded Neural Networks: Graph Neural PDE Solvers with Mixed Boundary Conditions

Masanobu Horie, NAOTO MITSUME

Quantum Algorithms for Sampling Log-Concave Distributions and Estimating Normalizing Constants

Andrew M. Childs, Tongyang Li, Jin-Peng Liu, Chunhao Wang, Ruizhe Zhang

PointNeXt: Revisiting PointNet++ with Improved Training and Scaling Strategies

Guocheng Qian, Yuchen Li, Houwen Peng, Jinjie Mai, Hasan Hammoud

Iso-Dream: Isolating and Leveraging Noncontrollable Visual Dynamics in World Models

Minting Pan, Xiangming Zhu, Yunbo Wang, Xiaokang Yang

Noise Attention Learning: Enhancing Noise Robustness by Gradient Scaling

Yangdi Lu, Yang Bo, Wenbo He

When to Update Your Model: Constrained Model-based Reinforcement Learning

Tianying Ji, Yu Luo, Fuchun Sun, Mingxuan Jing, Fengxiang He

Truncated proposals for scalable and hassle-free simulation-based inference

Michael Deistler, Pedro J Goncalves, Jakob H. Macke, Jakob H Macke

Bridging the Gap: Unifying the Training and Evaluation of Neural Network Binary Classifiers

Nathan Tsoi, Kate Candon, Deyuan Li, Yofti Milkessa, Marynel Vázquez

VITA: Video Instance Segmentation via Object Token Association

Miran Heo, Sukjun Hwang, Seoung Wug Oh, Joon-Young Lee, Seon Joo Kim

Parameter tuning and model selection in Optimal Transport with semi-dual Brenier formulation

Adrien Vacher, Francois-Xavier Vialard

Beyond accuracy: generalization properties of bio-plausible temporal credit assignment rules

Yuhan Helena Liu, Arna Ghosh, Blake Richards, Eric Shea-Brown, Guillaume Lajoie

Indicators of Attack Failure: Debugging and Improving Optimization of Adversarial Examples

Maura Pintor, Luca Demetrio, Angelo Sotgiu, Ambra Demontis, Nicholas Carlini

Towards Understanding the Mixture-of-Experts Layer in Deep Learning

Zixiang Chen, Yihe Deng, Yue Wu, Quanquan Gu, Yuanzhi Li

Signal Recovery with Non-Expansive Generative Network Priors

Jorio Cocola

The Missing Invariance Principle found -- the Reciprocal Twin of Invariant Risk Minimization

Dongsung Huh, Avinash Baidya

Generative Time Series Forecasting with Diffusion, Denoise, and Disentanglement

Yan Li, Xinjiang Lu, Yaqing Wang, Dejing Dou

Deep Fourier Up-Sampling

man zhou, Hu Yu, Jie Huang, Feng Zhao, Jinwei Gu

Diagonal State Spaces are as Effective as Structured State Spaces

Ankit Gupta, Albert Gu, Jonathan Berant

Performative Power

Moritz Hardt, Meena Jagadeesan, Celestine Mendler-Dünner

Behavior Transformers: Cloning k modes with one stone

Nur Muhammad Shafiullah, Zichen Cui, Ariuntuya (Arty) Altanzaya, Lerrel Pinto

On-Device Training Under 256KB Memory

Ji Lin, Ligeng Zhu, Wei-Ming Chen, Wei-Chen Wang, Chuang Gan

Hierarchical Agglomerative Graph Clustering in Poly-Logarithmic Depth

Laxman Dhulipala, David Eisenstat, Jakub Lacki, Vahab Mirrokni, Jessica Shi

Reconstructing Training Data From Trained Neural Networks

Niv Haim, Gal Vardi, Gilad Yehudai, Ohad Shamir, Michal Irani

Contrastive Language-Image Pre-Training with Knowledge Graphs

Xuran Pan, Tianzhu Ye, Dongchen Han, Shiji Song, Gao Huang

Kernel Interpolation with Sparse Grids

Mohit Yadav, Daniel R. Sheldon, Cameron Musco

Convergence for score-based generative modeling with polynomial complexity

Holden Lee, Jianfeng Lu, Yixin Tan

Shape, Light, and Material Decomposition from Images using Monte Carlo Rendering and Denoising

Jon Hasselgren, Nikolai Hofmann, Jacob Munkberg

A2: Efficient Automated Attacker for Boosting Adversarial Training

Zhuoer Xu, Guanghui Zhu, Changhua Meng, shiwen cui, Zhenzhe Ying

Robust Model Selection and Nearly-Proper Learning for GMMs

Allen Liu, Jerry Li, Ankur Moitra

Partial Identification of Treatment Effects with Implicit Generative Models

Vahid Balazadeh Meresht, Vasilis Syrgkanis, Rahul G Krishnan

Continuous Deep Q-Learning in Optimal Control Problems: Normalized Advantage Functions Analysis

Anton Plaksin, Stepan Martyanov

Escaping Saddle Points for Effective Generalization on Class-Imbalanced Data

Harsh Rangwani, Sumukh K Aithal, Mayank Mishra, Venkatesh Babu R

Globally Convergent Policy Search for Output Estimation

Jack Umenberger, Max Simchowitz, Juan Perdomo, Kaiqing Zhang, Russ Tedrake

DGraph: A Large-Scale Financial Dataset for Graph Anomaly Detection

Xuanwen Huang, Yang Yang, Yang Wang, Chunping Wang, Zhisheng Zhang

Physically-Based Face Rendering for NIR-VIS Face Recognition

Yunqi Miao, Alexandros Lattas, Jiankang Deng, Jungong Han, Stefanos Zafeiriou

Redistribution of Weights and Activations for AdderNet Quantization

Ying Nie, Kai Han, Haikang Diao, Chuanjian Liu, Enhua Wu

Expected Improvement for Contextual Bandits

Hung Tran-The, Sunil Gupta, Santu Rana, Tuan Truong, Long Tran-Thanh

Can Hybrid Geometric Scattering Networks Help Solve the Maximum Clique Problem?

Yimeng Min, Frederik Wenkel, Michael Perlmutter, Guy Wolf

BMU-MoCo: Bidirectional Momentum Update for Continual Video-Language Modeling

Yizhao Gao, Nanyi Fei, Haoyu Lu, Zhiwu Lu, Hao Jiang

Tractable Function-Space Variational Inference in Bayesian Neural Networks

Tim G. J. Rudner, Zonghao Chen, Yee Whye Teh, Yarin Gal

Hybrid Neural Autoencoders for Stimulus Encoding in Visual and Other Sensory Neuroprostheses

Jacob Granley, Lucas Relic, Michael Beyeler

Towards Out-of-Distribution Sequential Event Prediction: A Causal Treatment

Chenxiao Yang, Qitian Wu, Qingsong Wen, Zhiqiang Zhou, Liang Sun

Stochastic Multiple Target Sampling Gradient Descent

Hoang Phan, Ngoc Tran, Trung Le, Toan Tran, nhật Hồ

How Well Do Unsupervised Learning Algorithms Model Human Real-time and Life-long Learning?

Chengxu Zhuang, Ziyu Xiang, Yoon Bai, Xiaoxuan Jia, Nicholas Turk-Browne

Differentially Private Graph Learning via Sensitivity-Bounded Personalized PageRank

Alessandro Epasto, Vahab Mirrokni, Bryan Perozzi, Anton Tsitsulin, Peilin Zhong

Collaborative Linear Bandits with Adversarial Agents: Near-Optimal Regret Bounds

Aritra Mitra, Arman Adibi, George J. Pappas, Hamed Hassani

Zeroth-Order Hard-Thresholding: Gradient Error vs. Expansivity

William de Vazelhes, Hualin Zhang, Huimin Wu, Xiaotong Yuan, Bin Gu

Tracking Functional Changes in Nonstationary Signals with Evolutionary Ensemble Bayesian Model for Robust Neural Decoding

Xinyun Zhu, Yu Qi, Gang Pan, Yueming Wang

Alleviating "Posterior Collapse'' in Deep Topic Models via Policy Gradient

Yewen Li, Chaojie Wang, Zhibin Duan, Dongsheng Wang, Bo Chen

Efficient Adversarial Training without Attacking: Worst-Case-Aware Robust Reinforcement Learning

Yongyuan Liang, Yanchao Sun, Ruijie Zheng, Furong Huang

Domain Adaptation under Open Set Label Shift

Saurabh Garg, Sivaraman Balakrishnan, Zachary Lipton

GREED: A Neural Framework for Learning Graph Distance Functions

Rishabh Ranjan, Siddharth Grover, Sourav Medya, Venkatesan Chakaravarthy, Yogish Sabharwal

Differentially Private Generalized Linear Models Revisited

Raman Arora, Raef Bassily, Cristóbal Guzmán, Michael Menart, Enayat Ullah