ICML 2023

1,828 papers

Temporally Consistent Transformers for Video Generation

Wilson Yan, Danijar Hafner, Stephen James, Pieter Abbeel

Compressed Decentralized Proximal Stochastic Gradient Method for Nonconvex Composite Problems with Heterogeneous Data

Yonggui Yan, Jie Chen, Pin-Yu Chen, Xiaodong Cui, Songtao Lu

Quantum Ridgelet Transform: Winning Lottery Ticket of Neural Networks with Quantum Computation

Hayata Yamasaki, Sathyawageeswar Subramanian, Satoshi Hayakawa, Sho Sonoda

Q-learning Decision Transformer: Leveraging Dynamic Programming for Conditional Sequence Modelling in Offline RL

Taku Yamagata, Ahmed Khalil, Raul Santos-Rodriguez

Adaptive Computation with Elastic Input Sequence

Fuzhao Xue, Valerii Likhosherstov, Anurag Arnab, Neil Houlsby, Mostafa Dehghani

Which Features are Learnt by Contrastive Learning? On the Role of Simplicity Bias in Class Collapse and Feature Suppression

Yihao Xue, Siddharth Joshi, Eric Gan, Pin-Yu Chen, Baharan Mirzasoleiman

LazyGNN: Large-Scale Graph Neural Networks via Lazy Propagation

Rui Xue, Haoyu Han, MohamadAli Torkamani, Jian Pei, Xiaorui Liu

A Study on Transformer Configuration and Training Objective

Fuzhao Xue, Jianghai Chen, Aixin Sun, Xiaozhe Ren, Zangwei Zheng

Near-Optimal Quantum Coreset Construction Algorithms for Clustering

Yecheng Xue, Xiaoyu Chen, Tongyang Li, Shaofeng H.-C. Jiang

An Instrumental Variable Approach to Confounded Off-Policy Evaluation

Yang Xu, Jin Zhu, Chengchun Shi, Shikai Luo, Rui Song

Do Not Train It: A Linear Neural Architecture Search of Graph Neural Networks

Peng Xu, Lin Zhang, Xuanzhou Liu, Jiaqi Sun, Yue Zhao

SLAMB: Accelerated Large Batch Training with Sparse Communication

Hang Xu, Wenxuan Zhang, Jiawei Fei, Yuzhe Wu, Tingwen Xie

Bayesian Design Principles for Frequentist Sequential Learning

Yunbei Xu, Assaf Zeevi

ProtST: Multi-Modality Learning of Protein Sequences and Biomedical Texts

Minghao Xu, Xinyu Yuan, Santiago Miret, Jian Tang

mPLUG-2: A Modularized Multi-modal Foundation Model Across Text, Image and Video

Haiyang Xu, Qinghao Ye, Ming Yan, Yaya Shi, Jiabo Ye

Sequential Predictive Conformal Inference for Time Series

Chen Xu, Yao Xie

Competing for Shareable Arms in Multi-Player Multi-Armed Bandits

Renzhe Xu, Haotian Wang, Xingxuan Zhang, Bo Li, Peng Cui

Fascinating Supervisory Signals and Where to Find Them: Deep Anomaly Detection with Scale Learning

Hongzuo Xu, Yijie Wang, Juhui Wei, Songlei Jian, Yizhou Li

The Power of Preconditioning in Overparameterized Low-Rank Matrix Sensing

Xingyu Xu, Yandi Shen, Yuejie Chi, Cong Ma

Geometric Latent Diffusion Models for 3D Molecule Generation

Minkai Xu, Alexander S Powers, Ron O. Dror, Stefano Ermon, Jure Leskovec

PFGM++: Unlocking the Potential of Physics-Inspired Generative Models

Yilun Xu, Ziming Liu, Yonglong Tian, Shangyuan Tong, Max Tegmark

Progressive Purification for Instance-Dependent Partial Label Learning

Ning Xu, Biao Liu, Jiaqi Lv, Congyu Qiao, Xin Geng

Quantifying the Variability Collapse of Neural Networks

Jing Xu, Haoxiong Liu

Diverse and Faithful Knowledge-Grounded Dialogue Generation via Sequential Posterior Inference

Yan Xu, Deqian Kong, Dehong Xu, Ziwei Ji, Bo Pang

Pareto Regret Analyses in Multi-objective Multi-armed Bandit

Mengfan Xu, Diego Klabjan

Constrained Efficient Global Optimization of Expensive Black-box Functions

Wenjie Xu, Yuning Jiang, Bratislav Svetozarevic, Colin Jones

Efficient Sequence Transduction by Jointly Predicting Tokens and Durations

Hainan Xu, Fei Jia, Somshubra Majumdar, He Huang, Shinji Watanabe

Hierarchical Neural Coding for Controllable CAD Model Generation

Xiang Xu, Pradeep Kumar Jayaraman, Joseph George Lambourne, Karl D.D. Willis, Yasutaka Furukawa

Probabilistic Categorical Adversarial Attack and Adversarial Training

Han Xu, Pengfei He, Jie Ren, Yuxuan Wan, Zitao Liu

Regret Bounds for Markov Decision Processes with Recursive Optimized Certainty Equivalents

Wenhao Xu, Xuefeng GAO, Xuedong He

Bit Allocation using Optimization

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

MixFlows: principled variational inference via mixed flows

Zuheng Xu, Naitong Chen, Trevor Campbell

Why do Nearest Neighbor Language Models Work?

Frank F. Xu, Uri Alon, Graham Neubig

Relevant Walk Search for Explaining Graph Neural Networks

Ping Xiong, Thomas Schnake, Michael Gastegger, Grégoire Montavon, Klaus Robert Muller

Universal Morphology Control via Contextual Modulation

Zheng Xiong, Jacob Beck, Shimon Whiteson

Controlling Type Confounding in Ad Hoc Teamwork with Instance-wise Teammate Feedback Rectification

Dong Xing, Pengjie Gu, Qian Zheng, Xinrun Wang, Shanqi Liu

A Critical View of Vision-Based Long-Term Dynamics Prediction Under Environment Misalignment

Hanchen Xie, Jiageng Zhu, Mahyar Khayatkhoei, Jiazhi Li, Mohamed E. Hussein

Semiparametrically Efficient Off-Policy Evaluation in Linear Markov Decision Processes

Chuhan Xie, Wenhao Yang, Zhihua Zhang

DeSRA: Detect and Delete the Artifacts of GAN-based Real-World Super-Resolution Models

Liangbin Xie, Xintao Wang, Xiangyu Chen, Gen Li, Ying Shan

Future-conditioned Unsupervised Pretraining for Decision Transformer

Zhihui Xie, Zichuan Lin, Deheng Ye, Qiang Fu, Yang Wei

Improving Bi-level Optimization Based Methods with Inspiration from Humans’ Classroom Study Techniques

Pengtao Xie

COMCAT: Towards Efficient Compression and Customization of Attention-Based Vision Models

Jinqi Xiao, Miao Yin, Yu Gong, Xiao Zang, Jian Ren

On the Forward Invariance of Neural ODEs

Wei Xiao, Tsun-Hsuan Wang, Ramin Hasani, Mathias Lechner, Yutong Ban

SmoothQuant: Accurate and Efficient Post-Training Quantization for Large Language Models

Guangxuan Xiao, Ji Lin, Mickael Seznec, Hao Wu, Julien Demouth

Communication-Efficient Federated Hypergradient Computation via Aggregated Iterative Differentiation

Peiyao Xiao, Kaiyi Ji

Random Shuffle Transformer for Image Restoration

Jie Xiao, Xueyang Fu, man zhou, Hongjian Liu, Zheng-Jun Zha

UMD: Unsupervised Model Detection for X2X Backdoor Attacks

Zhen Xiang, Zidi Xiong, Bo Li

Fair and Optimal Classification via Post-Processing

Ruicheng Xian, Lang Yin, Han Zhao

Understanding Backdoor Attacks through the Adaptability Hypothesis

Xun Xian, Ganghua Wang, Jayanth Srinivasa, Ashish Kundu, Xuan Bi

Finite-Sample Analysis of Learning High-Dimensional Single ReLU Neuron

Jingfeng Wu, Difan Zou, Zixiang Chen, Vladimir braverman, Quanquan Gu

Differentially Private Episodic Reinforcement Learning with Heavy-tailed Rewards

Yulian Wu, Xingyu Zhou, Sayak Ray Chowdhury, Di Wang

Personalized Federated Learning under Mixture of Distributions

Yue Wu, Shuaicheng Zhang, Wenchao Yu, Yanchi Liu, Quanquan Gu

dugMatting: Decomposed-Uncertainty-Guided Matting

Jiawei Wu, Changqing Zhang, Zuoyong Li, Huazhu Fu, Xi Peng

On the Training Instability of Shuffling SGD with Batch Normalization

David Xing Wu, Chulhee Yun, Suvrit Sra

Discover and Cure: Concept-aware Mitigation of Spurious Correlation

Shirley Wu, Mert Yuksekgonul, Linjun Zhang, James Zou

QuantumDARTS: Differentiable Quantum Architecture Search for Variational Quantum Algorithms

Wenjie Wu, Ge Yan, Xudong Lu, Kaisen Pan, Junchi Yan

Learning Functional Distributions with Private Labels

Changlong Wu, Yifan Wang, Ananth Grama, Wojciech Szpankowski

π-Tuning: Transferring Multimodal Foundation Models with Optimal Multi-task Interpolation

Chengyue Wu, Teng Wang, Yixiao Ge, Zeyu Lu, Ruisong Zhou

Distributional Offline Policy Evaluation with Predictive Error Guarantees

Runzhe Wu, Masatoshi Uehara, Wen Sun

The Implicit Regularization of Dynamical Stability in Stochastic Gradient Descent

Lei Wu, Weijie J Su

Tight Data Access Bounds for Private Top-k Selection

Hao Wu, Olga Ohrimenko, Anthony Wirth

Disentangled Multi-Fidelity Deep Bayesian Active Learning

Dongxia Wu, Ruijia Niu, Matteo Chinazzi, Yian Ma, Rose Yu

Masked Trajectory Models for Prediction, Representation, and Control

Philipp Wu, Arjun Majumdar, Kevin Stone, Yixin Lin, Igor Mordatch

Delay-agnostic Asynchronous Coordinate Update Algorithm

Xuyang Wu, Changxin Liu, Sindri Magnússon, Mikael Johansson

Quantifying the Knowledge in GNNs for Reliable Distillation into MLPs

Lirong Wu, Haitao Lin, Yufei Huang, Stan Z. Li

Towards Understanding Generalization of Macro-AUC in Multi-label Learning

Guoqiang Wu, Chongxuan Li, Yilong Yin

Understanding Int4 Quantization for Language Models: Latency Speedup, Composability, and Failure Cases

Xiaoxia Wu, Cheng Li, Reza Yazdani Aminabadi, Zhewei Yao, Yuxiong He

Rethinking Explaining Graph Neural Networks via Non-parametric Subgraph Matching

Fang Wu, Siyuan Li, Xurui Jin, Yinghui Jiang, Dragomir Radev

Stable Estimation of Heterogeneous Treatment Effects

Anpeng Wu, Kun Kuang, Ruoxuan Xiong, Bo Li, Fei Wu

Uncovering Adversarial Risks of Test-Time Adaptation

Tong Wu, Feiran Jia, Xiangyu Qi, Jiachen T. Wang, Vikash Sehwag

A Law of Robustness beyond Isoperimetry

Yihan Wu, Heng Huang, Hongyang Zhang

Solving High-Dimensional PDEs with Latent Spectral Models

Haixu Wu, Tengge Hu, Huakun Luo, Jianmin Wang, Mingsheng Long

Anchor Sampling for Federated Learning with Partial Client Participation

Feijie Wu, Song Guo, Zhihao Qu, Shiqi He, Ziming Liu

Adaptive Compositional Continual Meta-Learning

Bin Wu, Jinyuan Fang, Xiangxiang Zeng, Shangsong Liang, Qiang Zhang

Effective Neural Topic Modeling with Embedding Clustering Regularization

Xiaobao Wu, Xinshuai Dong, Thong Thanh Nguyen, Anh Tuan Luu

Causal Proxy Models for Concept-based Model Explanations

Zhengxuan Wu, Karel D’Oosterlinck, Atticus Geiger, Amir Zur, Christopher Potts

SEGA: Structural Entropy Guided Anchor View for Graph Contrastive Learning

Junran Wu, Xueyuan Chen, Bowen Shi, Shangzhe Li, Ke Xu

Two Losses Are Better Than One: Faster Optimization Using a Cheaper Proxy

Blake Woodworth, Konstantin Mishchenko, Francis Bach

Sharper Bounds for ℓ_p Sensitivity Sampling

David Woodruff, Taisuke Yasuda

Learning Deep Time-index Models for Time Series Forecasting

Gerald Woo, Chenghao Liu, Doyen Sahoo, Akshat Kumar, Steven Hoi

The Blessing of Heterogeneity in Federated Q-Learning: Linear Speedup and Beyond

Jiin Woo, Gauri Joshi, Yuejie Chi

Uncertainty Estimation for Molecules: Desiderata and Methods

Tom Wollschläger, Nicholas Gao, Bertrand Charpentier, Mohamed Amine Ketata, Stephan Günnemann

Marginalization is not Marginal: No Bad VAE Local Minima when Learning Optimal Sparse Representations

David Wipf

Theoretical Behavior of XAI Methods in the Presence of Suppressor Variables

Rick Wilming, Leo Kieslich, Benedict Clark, Stefan Haufe

Approximate Stein Classes for Truncated Density Estimation

Daniel James Williams, Song Liu

Flexible Phase Dynamics for Bio-Plausible Contrastive Learning

Ezekiel Williams, Colin Bredenberg, Guillaume Lajoie

Scalable Set Encoding with Universal Mini-Batch Consistency and Unbiased Full Set Gradient Approximation

Jeffrey Willette, Seanie Lee, Bruno Andreis, Kenji Kawaguchi, Juho Lee

Fully-Adaptive Composition in Differential Privacy

Justin Whitehouse, Aaditya Ramdas, Ryan Rogers, Steven Wu

Open-VCLIP: Transforming CLIP to an Open-vocabulary Video Model via Interpolated Weight Optimization

Zejia Weng, Xitong Yang, Ang Li, Zuxuan Wu, Yu-Gang Jiang

Towards Learning Geometric Eigen-Lengths Crucial for Fitting Tasks

Yijia Weng, Kaichun Mo, Ruoxi Shi, Yanchao Yang, Leonidas Guibas

Optimizing Mode Connectivity for Class Incremental Learning

Haitao Wen, Haoyang Cheng, Heqian Qiu, Lanxiao Wang, Lili Pan

A Conditional Normalizing Flow for Accelerated Multi-Coil MR Imaging

Jeffrey Wen, Rizwan Ahmad, Philip Schniter

Expectation-Complete Graph Representations with Homomorphisms

Pascal Welke, Maximilian Thiessen, Fabian Jogl, Thomas Gärtner

Graphically Structured Diffusion Models

Christian Dietrich Weilbach, William Harvey, Frank Wood

Mitigating Memorization of Noisy Labels by Clipping the Model Prediction

Hongxin Wei, HUIPING ZHUANG, RENCHUNZI XIE, Lei Feng, Gang Niu

Set-membership Belief State-based Reinforcement Learning for POMDPs

Wei Wei, Lijun Zhang, Lin Li, Huizhong Song, Jiye Liang

Boosting Graph Contrastive Learning via Graph Contrastive Saliency

Chunyu Wei, Yu Wang, Bing Bai, Kai Ni, David Brady

NTK-approximating MLP Fusion for Efficient Language Model Fine-tuning

Tianxin Wei, Zeming Guo, Yifan Chen, Jingrui He

A Universal Unbiased Method for Classification from Aggregate Observations

Zixi Wei, Lei Feng, Bo Han, Tongliang Liu, Gang Niu

Global optimality for Euclidean CCCP under Riemannian convexity

Melanie Weber, Suvrit Sra