ICML 2023

1,828 papers

Adaptive Barrier Smoothing for First-Order Policy Gradient with Contact Dynamics

Shenao Zhang, Wanxin Jin, Zhaoran Wang

CAB: Comprehensive Attention Benchmarking on Long Sequence Modeling

Jun Zhang, Shuyang Jiang, Jiangtao Feng, Lin Zheng, Lingpeng Kong

Towards Coherent Image Inpainting Using Denoising Diffusion Implicit Models

Guanhua Zhang, Jiabao Ji, Yang Zhang, Mo Yu, Tommi Jaakkola

Spatial-Temporal Graph Learning with Adversarial Contrastive Adaptation

Qianru Zhang, Chao Huang, Lianghao Xia, Zheng Wang, Siu Ming Yiu

When Sparsity Meets Contrastive Models: Less Graph Data Can Bring Better Class-Balanced Representations

Chunhui Zhang, Chao Huang, Yijun Tian, Qianlong Wen, Zhongyu Ouyang

On the Interplay Between Misspecification and Sub-optimality Gap in Linear Contextual Bandits

Weitong ZHANG, Jiafan He, Zhiyuan Fan, Quanquan Gu

Prompting Large Language Model for Machine Translation: A Case Study

Biao Zhang, Barry Haddow, Alexandra Birch

Crafting Training Degradation Distribution for the Accuracy-Generalization Trade-off in Real-World Super-Resolution

Ruofan Zhang, Jinjin Gu, Haoyu Chen, Chao Dong, Yulun Zhang

A Complete Expressiveness Hierarchy for Subgraph GNNs via Subgraph Weisfeiler-Lehman Tests

Bohang Zhang, Guhao Feng, Yiheng Du, Di He, Liwei Wang

Team Belief DAG: Generalizing the Sequence Form to Team Games for Fast Computation of Correlated Team Max-Min Equilibria via Regret Minimization

Brian Hu Zhang, Gabriele Farina, Tuomas Sandholm

Rethink DARTS Search Space and Renovate a New Benchmark

Jiuling Zhang, Zhiming Ding

CataBEEM: Integrating Latent Interaction Categories in Node-wise Community Detection Models for Network Data

Yuhua Zhang, Walter H. Dempsey

Tractable Control for Autoregressive Language Generation

Honghua Zhang, Meihua Dang, Nanyun Peng, Guy Van den Broeck

Effective Minkowski Dimension of Deep Nonparametric Regression: Function Approximation and Statistical Theories

Zixuan Zhang, Minshuo Chen, Mengdi Wang, Wenjing Liao, Tuo Zhao

Graph Contrastive Backdoor Attacks

Hangfan Zhang, Jinghui Chen, Lu Lin, Jinyuan Jia, Dinghao Wu

Matrix Estimation for Individual Fairness

Cindy Zhang, Sarah Huiyi Cen, Devavrat Shah

Nonparametric Iterative Machine Teaching

Chen Zhang, Xiaofeng Cao, Weiyang Liu, Ivor Tsang, James Kwok

Learning useful representations for shifting tasks and distributions

Jianyu Zhang, Léon Bottou

Offline Learning in Markov Games with General Function Approximation

Yuheng Zhang, Yu Bai, Nan Jiang

Stabilizing Transformer Training by Preventing Attention Entropy Collapse

Shuangfei Zhai, Tatiana Likhomanenko, Etai Littwin, Dan Busbridge, Jason Ramapuram

Generative Graph Dictionary Learning

Zhichen Zeng, Ruike Zhu, Yinglong Xia, Hanqing Zeng, Hanghang Tong

Attribute-Efficient PAC Learning of Low-Degree Polynomial Threshold Functions with Nasty Noise

Shiwei Zeng, Jie Shen

LookupFFN: Making Transformers Compute-lite for CPU inference

Zhanpeng Zeng, Michael Davies, Pranav Pulijala, Karthikeyan Sankaralingam, Vikas Singh

Sequential Counterfactual Risk Minimization

Houssam Zenati, Eustache Diemert, Matthieu Martin, Julien Mairal, Pierre Gaillard

On Distribution Dependent Sub-Logarithmic Query Time of Learned Indexing

Sepanta Zeighami, Cyrus Shahabi

When is Realizability Sufficient for Off-Policy Reinforcement Learning?

Andrea Zanette

Bayesian Estimation of Differential Privacy

Santiago Zanella-Beguelin, Lukas Wutschitz, Shruti Tople, Ahmed Salem, Victor Rühle

KDEformer: Accelerating Transformers via Kernel Density Estimation

Amir Zandieh, Insu Han, Majid Daliri, Amin Karbasi

Conformal Prediction with Missing Values

Margaux Zaffran, Aymeric Dieuleveut, Julie Josse, Yaniv Romano

Traversing Between Modes in Function Space for Fast Ensembling

Eunggu Yun, Hyungi Lee, Giung Nam, Juho Lee

Automatic Intrinsic Reward Shaping for Exploration in Deep Reinforcement Learning

Mingqi Yuan, Bo Li, Xin Jin, Wenjun Zeng

On the Power of Foundation Models

Yang Yuan

Coordinate Descent Methods for Fractional Minimization

Ganzhao Yuan

Master-ASR: Achieving Multilingual Scalability and Low-Resource Adaptation in ASR with Modular Learning

Zhongzhi Yu, Yang Zhang, Kaizhi Qian, Cheng Wan, Yonggan Fu

Actor-Critic Alignment for Offline-to-Online Reinforcement Learning

Zishun Yu, Xinhua Zhang

On the Global Convergence of Risk-Averse Policy Gradient Methods with Expected Conditional Risk Measures

Xian Yu, Lei Ying

Efficient and Equivariant Graph Networks for Predicting Quantum Hamiltonian

Haiyang Yu, Zhao Xu, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji

SeedGNN: Graph Neural Network for Supervised Seeded Graph Matching

Liren Yu, Jiaming Xu, Xiaojun Lin

CodeIPPrompt: Intellectual Property Infringement Assessment of Code Language Models

Zhiyuan Yu, Yuhao Wu, Ning Zhang, Chenguang Wang, Yevgeniy Vorobeychik

Adversarial Parameter Attack on Deep Neural Networks

Lijia Yu, Yihan Wang, Xiao-Shan Gao

Long-Term Rhythmic Video Soundtracker

Jiashuo Yu, Yaohui Wang, Xinyuan Chen, Xiao Sun, Yu Qiao

Discover-Then-Rank Unlabeled Support Vectors in the Dual Space for Multi-Class Active Learning

Dayou Yu, Weishi Shi, Qi Yu

Bag of Tricks for Training Data Extraction from Language Models

Weichen Yu, Tianyu Pang, Qian Liu, Chao Du, Bingyi Kang

Delving into Noisy Label Detection with Clean Data

Chenglin Yu, Xinsong Ma, Weiwei Liu

COLA: Orchestrating Error Coding and Learning for Robust Neural Network Inference Against Hardware Defects

Anlan Yu, Ning Lyu, Jieming Yin, Zhiyuan Yan, Wujie Wen

The Benefits of Model-Based Generalization in Reinforcement Learning

Kenny John Young, Aditya Ramesh, Louis Kirsch, Jürgen Schmidhuber

Entropy-driven Unsupervised Keypoint Representation Learning in Videos

Ali Younes, Simone Schaub-Meyer, Georgia Chalvatzaki

Analyzing Convergence in Quantum Neural Networks: Deviations from Neural Tangent Kernels

Xuchen You, Shouvanik Chakrabarti, Boyang Chen, Xiaodi Wu

Graph Generative Model for Benchmarking Graph Neural Networks

Minji Yoon, Yue Wu, John Palowitch, Bryan Perozzi, Russ Salakhutdinov

An Investigation into Pre-Training Object-Centric Representations for Reinforcement Learning

Jaesik Yoon, Yi-Fu Wu, Heechul Bae, Sungjin Ahn

Continual Learners are Incremental Model Generalizers

Jaehong Yoon, Sung Ju Hwang, Yue Cao

EM-Network: Oracle Guided Self-distillation for Sequence Learning

Ji Won Yoon, Sunghwan Ahn, Hyeonseung Lee, Minchan Kim, Seok Min Kim

End-to-End Multi-Object Detection with a Regularized Mixture Model

Jaeyoung Yoo, Hojun Lee, Seunghyeon Seo, Inseop Chung, Nojun Kwak

Improving Visual Prompt Tuning for Self-supervised Vision Transformers

Seungryong Yoo, Eunji Kim, Dahuin Jung, Jungbeom Lee, Sungroh Yoon

Adaptive Estimation of Graphical Models under Total Positivity

Jiaxi Ying, José Vinı́cius De Miranda Cardoso, Daniel P. Palomar

CoCo: A Coupled Contrastive Framework for Unsupervised Domain Adaptive Graph Classification

Nan Yin, Li Shen, Mengzhu Wang, Long Lan, Zeyu Ma

SE(3) diffusion model with application to protein backbone generation

Jason Yim, Brian L. Trippe, Valentin De Bortoli, Emile Mathieu, Arnaud Doucet

MonoFlow: Rethinking Divergence GANs via the Perspective of Wasserstein Gradient Flows

Mingxuan Yi, Zhanxing Zhu, Song Liu

Online Prototype Alignment for Few-shot Policy Transfer

Qi Yi, Rui Zhang, shaohui peng, Jiaming Guo, Yunkai Gao

Doubly Adversarial Federated Bandits

Jialin Yi, Milan Vojnovic

From Temporal to Contemporaneous Iterative Causal Discovery in the Presence of Latent Confounders

Raanan Yehezkel Rohekar, Shami Nisimov, Yaniv Gurwicz, Gal Novik

Temporal Label Smoothing for Early Event Prediction

Hugo Yèche, Alizée Pace, Gunnar Rätsch, Rita Kuznetsova

Towards Quantum Machine Learning for Constrained Combinatorial Optimization: a Quantum QAP Solver

Xinyu Ye, Ge Yan, Junchi Yan

FedDisco: Federated Learning with Discrepancy-Aware Collaboration

Rui Ye, Mingkai Xu, Jianyu Wang, Chenxin Xu, Siheng Chen

GNN&GBDT-Guided Fast Optimizing Framework for Large-scale Integer Programming

Huigen Ye, Hua Xu, Hongyan Wang, Chengming Wang, Yu Jiang

Corruption-Robust Algorithms with Uncertainty Weighting for Nonlinear Contextual Bandits and Markov Decision Processes

Chenlu Ye, Wei Xiong, Quanquan Gu, Tong Zhang

Compositional Exemplars for In-context Learning

Jiacheng Ye, Zhiyong Wu, Jiangtao Feng, Tao Yu, Lingpeng Kong

Personalized Federated Learning with Inferred Collaboration Graphs

Rui Ye, Zhenyang Ni, Fangzhao Wu, Siheng Chen, Yanfeng Wang

On the Power of Pre-training for Generalization in RL: Provable Benefits and Hardness

Haotian Ye, Xiaoyu Chen, Liwei Wang, Simon Shaolei Du

Retrieval-Augmented Multimodal Language Modeling

Michihiro Yasunaga, Armen Aghajanyan, Weijia Shi, Richard James, Jure Leskovec

Policy Mirror Ascent for Efficient and Independent Learning in Mean Field Games

Batuhan Yardim, Semih Cayci, Matthieu Geist, Niao He

MultiAdam: Parameter-wise Scale-invariant Optimizer for Multiscale Training of Physics-informed Neural Networks

Jiachen Yao, Chang Su, Zhongkai Hao, Songming Liu, Hang Su

How Bad is Top-K Recommendation under Competing Content Creators?

Fan Yao, Chuanhao Li, Denis Nekipelov, Hongning Wang, Haifeng Xu

Which is Better for Learning with Noisy Labels: The Semi-supervised Method or Modeling Label Noise?

Yu Yao, Mingming Gong, Yuxuan Du, Jun Yu, Bo Han

Hyperbolic Representation Learning: Revisiting and Advancing

Menglin Yang, Min Zhou, Rex Ying, yankai Chen, Irwin King

Continual Task Allocation in Meta-Policy Network via Sparse Prompting

Yijun Yang, Tianyi Zhou, Jing Jiang, Guodong Long, Yuhui Shi

Change is Hard: A Closer Look at Subpopulation Shift

Yuzhe Yang, Haoran Zhang, Dina Katabi, Marzyeh Ghassemi

Neural Prediction Errors enable Analogical Visual Reasoning in Human Standard Intelligence Tests

Lingxiao Yang, Hongzhi You, Zonglei Zhen, Dahui Wang, Xiaohong Wan

What is Essential for Unseen Goal Generalization of Offline Goal-conditioned RL?

Rui Yang, LIN Yong, Xiaoteng Ma, Hao Hu, Chongjie Zhang

Towards Controlled Data Augmentations for Active Learning

Jianan Yang, Haobo Wang, Sai Wu, Gang Chen, Junbo Zhao

Boosting Offline Reinforcement Learning with Action Preference Query

Qisen Yang, Shenzhi Wang, Matthieu Gaetan Lin, Shiji Song, Gao Huang

Generative Adversarial Symmetry Discovery

Jianke Yang, Robin Walters, Nima Dehmamy, Rose Yu

Are Neurons Actually Collapsed? On the Fine-Grained Structure in Neural Representations

Yongyi Yang, Jacob Steinhardt, Wei Hu

Efficient Algorithms for Exact Graph Matching on Correlated Stochastic Block Models with Constant Correlation

Joonhyuk Yang, Dongpil Shin, Hye Won Chung

A theory of representation learning gives a deep generalisation of kernel methods

Adam X. Yang, Maxime Robeyns, Edward Milsom, Ben Anson, Nandi Schoots

Mitigating Spurious Correlations in Multi-modal Models during Fine-tuning

Yu Yang, Besmira Nushi, Hamid Palangi, Baharan Mirzasoleiman

Improving Adversarial Robustness of Deep Equilibrium Models with Explicit Regulations Along the Neural Dynamics

Zonghan Yang, Peng Li, Tianyu Pang, Yang Liu

Improving Adversarial Robustness by Putting More Regularizations on Less Robust Samples

Dongyoon Yang, Insung Kong, Yongdai Kim

Towards Sustainable Learning: Coresets for Data-efficient Deep Learning

Yu Yang, Hao Kang, Baharan Mirzasoleiman

Data Poisoning Attacks Against Multimodal Encoders

Ziqing Yang, Xinlei He, Zheng Li, Michael Backes, Mathias Humbert

Chemically Transferable Generative Backmapping of Coarse-Grained Proteins

Soojung Yang, Rafael Gomez-Bombarelli

Weighted Flow Diffusion for Local Graph Clustering with Node Attributes: an Algorithm and Statistical Guarantees

Shenghao Yang, Kimon Fountoulakis

Towards Better Graph Representation Learning with Parameterized Decomposition & Filtering

Mingqi Yang, Wenjie Feng, Yanming Shen, Bryan Hooi

Nested Elimination: A Simple Algorithm for Best-Item Identification From Choice-Based Feedback

Junwen Yang, Yifan Feng

Behavior Contrastive Learning for Unsupervised Skill Discovery

Rushuai Yang, Chenjia Bai, Hongyi Guo, Siyuan Li, Bin Zhao

Proper Scoring Rules for Survival Analysis

Hiroki Yanagisawa

Fast Rates in Time-Varying Strongly Monotone Games

Yu-Hu Yan, Peng Zhao, Zhi-Hua Zhou

Quantum 3D Graph Learning with Applications to Molecule Embedding

Ge Yan, Huaijin Wu, Junchi Yan

Self-Interpretable Time Series Prediction with Counterfactual Explanations

Jingquan Yan, Hao Wang

Distortion and Uncertainty Aware Loss for Panoramic Depth Completion

Zhiqiang Yan, Xiang Li, Kun Wang, Shuo Chen, Jun Li