ICML 2023

1,828 papers

Active Policy Improvement from Multiple Black-box Oracles

Xuefeng Liu, Takuma Yoneda, Chaoqi Wang, Matthew Walter, Yuxin Chen

Optimization for Amortized Inverse Problems

Tianci Liu, Tong Yang, Quan Zhang, Qi Lei

Online Nonstochastic Control with Adversarial and Static Constraints

Xin Liu, Zixian Yang, Lei Ying

Retrosynthetic Planning with Dual Value Networks

Guoqing Liu, Di Xue, Shufang Xie, Yingce Xia, Austin Tripp

Revisiting Pseudo-Label for Single-Positive Multi-Label Learning

Biao Liu, Ning Xu, Jiaqi Lv, Xin Geng

Dropout Reduces Underfitting

Zhuang Liu, Zhiqiu Xu, Joseph Jin, Zhiqiang Shen, Trevor Darrell

Taxonomy-Structured Domain Adaptation

Tianyi Liu, Zihao Xu, Hao He, Guang-Yuan Hao, Guang-He Lee

Same Pre-training Loss, Better Downstream: Implicit Bias Matters for Language Models

Hong Liu, Sang Michael Xie, Zhiyuan Li, Tengyu Ma

Trapdoor Normalization with Irreversible Ownership Verification

Hanwen Liu, Zhenyu Weng, Yuesheng Zhu, Yadong Mu

Deja Vu: Contextual Sparsity for Efficient LLMs at Inference Time

Zichang Liu, Jue Wang, Tri Dao, Tianyi Zhou, Binhang Yuan

Global Optimization with Parametric Function Approximation

Chong Liu, Yu-Xiang Wang

TR0N: Translator Networks for 0-Shot Plug-and-Play Conditional Generation

Zhaoyan Liu, Noël Vouitsis, Satya Krishna Gorti, Jimmy Ba, Gabriel Loaiza-Ganem

What can online reinforcement learning with function approximation benefit from general coverage conditions?

Fanghui Liu, Luca Viano, Volkan Cevher

I$^2$SB: Image-to-Image Schrödinger Bridge

Guan-Horng Liu, Arash Vahdat, De-An Huang, Evangelos Theodorou, Weili Nie

FusionRetro: Molecule Representation Fusion via In-Context Learning for Retrosynthetic Planning

Songtao Liu, Zhengkai Tu, Minkai Xu, Zuobai Zhang, Lu Lin

Generating Private Synthetic Data with Genetic Algorithms

Terrance Liu, Jingwu Tang, Giuseppe Vietri, Steven Wu

Simple Embodied Language Learning as a Byproduct of Meta-Reinforcement Learning

Evan Zheran Liu, Sahaana Suri, Tong Mu, Allan Zhou, Chelsea Finn

Algorithms for bounding contribution for histogram estimation under user-level privacy

Yuhan Liu, Ananda Theertha Suresh, Wennan Zhu, Peter Kairouz, Marco Gruteser

RSC: Accelerate Graph Neural Networks Training via Randomized Sparse Computations

Zirui Liu, CHEN SHENGYUAN, Kaixiong Zhou, Daochen Zha, Xiao Huang

Lazy Agents: A New Perspective on Solving Sparse Reward Problem in Multi-agent Reinforcement Learning

Boyin Liu, Zhiqiang Pu, Yi Pan, Jianqiang Yi, Yanyan Liang

OMS-DPM: Optimizing the Model Schedule for Diffusion Probabilistic Models

Enshu Liu, Xuefei Ning, Zinan Lin, Huazhong Yang, Yu Wang

High Probability Convergence of Stochastic Gradient Methods

Zijian Liu, Ta Duy Nguyen, Thien Hang Nguyen, Alina Ene, Huy Nguyen

Graph Switching Dynamical Systems

Yongtuo Liu, Sara Magliacane, Miltiadis Kofinas, Efstratios Gavves

Averaged Method of Multipliers for Bi-Level Optimization without Lower-Level Strong Convexity

Risheng Liu, Yaohua Liu, Wei Yao, Shangzhi Zeng, Jin Zhang

Understanding the Distillation Process from Deep Generative Models to Tractable Probabilistic Circuits

Xuejie Liu, Anji Liu, Guy Van den Broeck, Yitao Liang

Oscillation-free Quantization for Low-bit Vision Transformers

Shih-Yang Liu, Zechun Liu, Kwang-Ting Cheng

Dink-Net: Neural Clustering on Large Graphs

Yue Liu, Ke Liang, Jun Xia, sihang zhou, Xihong Yang

Structural Re-weighting Improves Graph Domain Adaptation

Shikun Liu, Tianchun Li, Yongbin Feng, Nhan Tran, Han Zhao

Causal Structure Learning for Latent Intervened Non-stationary Data

Chenxi Liu, Kun Kuang

2D-Shapley: A Framework for Fragmented Data Valuation

Zhihong Liu, Hoang Anh Just, Xiangyu Chang, Xi Chen, Ruoxi Jia

GFlowOut: Dropout with Generative Flow Networks

Dianbo Liu, Moksh Jain, Bonaventure F. P. Dossou, Qianli Shen, Salem Lahlou

Online Local Differential Private Quantile Inference via Self-normalization

Yi Liu, Qirui Hu, Lei Ding, Linglong Kong

Hierarchical Programmatic Reinforcement Learning via Learning to Compose Programs

Guan-Ting Liu, En-Pei Hu, Pu-Jen Cheng, Hung-yi Lee, Shao-Hua Sun

NUNO: A General Framework for Learning Parametric PDEs with Non-Uniform Data

Songming Liu, Zhongkai Hao, Chengyang Ying, Hang Su, Ze Cheng

Understanding and Defending Patched-based Adversarial Attacks for Vision Transformer

Liang Liu, Yanan Guo, Youtao Zhang, Jun Yang

Constrained Decision Transformer for Offline Safe Reinforcement Learning

ZUXIN LIU, Zijian Guo, Yihang Yao, Zhepeng Cen, Wenhao Yu

Towards Robust and Safe Reinforcement Learning with Benign Off-policy Data

ZUXIN LIU, Zijian Guo, Zhepeng Cen, Huan Zhang, Yihang Yao

Opponent-Limited Online Search for Imperfect Information Games

Weiming Liu, Haobo Fu, Qiang Fu, Yang Wei

Cones: Concept Neurons in Diffusion Models for Customized Generation

Zhiheng Liu, Ruili Feng, Kai Zhu, Yifei Zhang, Kecheng Zheng

Using Perturbation to Improve Goodness-of-Fit Tests based on Kernelized Stein Discrepancy

Xing Liu, Andrew B. Duncan, Axel Gandy

A Group Symmetric Stochastic Differential Equation Model for Molecule Multi-modal Pretraining

Shengchao Liu, weitao Du, Zhi-ming Ma, Hongyu Guo, Jian Tang

Identifiability of Label Noise Transition Matrix

Yang Liu, Hao Cheng, Kun Zhang

AudioLDM: Text-to-Audio Generation with Latent Diffusion Models

Haohe Liu, Zehua Chen, Yi Yuan, Xinhao Mei, Xubo Liu

Towards Constituting Mathematical Structures for Learning to Optimize

Jialin Liu, Xiaohan Chen, Zhangyang Wang, Wotao Yin, HanQin Cai

Byzantine-Robust Learning on Heterogeneous Data via Gradient Splitting

Yuchen Liu, Chen Chen, Lingjuan Lyu, Fangzhao Wu, Sai Wu

Learning Representations without Compositional Assumptions

Tennison Liu, Jeroen Berrevoets, Zhaozhi Qian, Mihaela van der Schaar

Shapley Based Residual Decomposition for Instance Analysis

Tommy Liu, Amanda S Barnard

Emergent Agentic Transformer from Chain of Hindsight Experience

Hao Liu, Pieter Abbeel

Deep Graph Representation Learning and Optimization for Influence Maximization

Chen Ling, Junji Jiang, Junxiang Wang, My T. Thai, Renhao Xue

Graph Mixup with Soft Alignments

Hongyi Ling, Zhimeng Jiang, Meng Liu, Shuiwang Ji, Na Zou

Speed-Oblivious Online Scheduling: Knowing (Precise) Speeds is not Necessary

Alexander Lindermayr, Nicole Megow, Martin Rapp

Continuation Path Learning for Homotopy Optimization

Xi Lin, Zhiyuan Yang, Xiaoyuan Zhang, Qingfu Zhang

Efficient Approximations of Complete Interatomic Potentials for Crystal Property Prediction

Yuchao Lin, Keqiang Yan, Youzhi Luo, Yi Liu, Xiaoning Qian

Fair yet Asymptotically Equal Collaborative Learning

Xiaoqiang Lin, Xinyi Xu, See-Kiong Ng, Chuan-Sheng Foo, Bryan Kian Hsiang Low

Unveiling The Mask of Position-Information Pattern Through the Mist of Image Features

Chieh Hubert Lin, Hung-Yu Tseng, Hsin-Ying Lee, Maneesh Kumar Singh, Ming-Hsuan Yang

Fast Online Value-Maximizing Prediction Sets with Conformal Cost Control

Zhen Lin, Shubhendu Trivedi, Cao Xiao, Jimeng Sun

Probabilistic Unrolling: Scalable, Inverse-Free Maximum Likelihood Estimation for Latent Gaussian Models

Alexander Lin, Bahareh Tolooshams, Yves Atchade, Demba E. Ba

Safe Offline Reinforcement Learning with Real-Time Budget Constraints

Qian Lin, Bo Tang, Zifan Wu, Chao Yu, Shangqin Mao

Accelerated Cyclic Coordinate Dual Averaging with Extrapolation for Composite Convex Optimization

Cheuk Yin Lin, Chaobing Song, Jelena Diakonikolas

Theory on Forgetting and Generalization of Continual Learning

Sen Lin, Peizhong Ju, Yingbin Liang, Ness Shroff

Self-supervised Neural Factor Analysis for Disentangling Utterance-level Speech Representations

Weiwei Lin, Chenhang He, Man-Wai Mak, Youzhi Tu

Text Generation with Diffusion Language Models: A Pre-training Approach with Continuous Paragraph Denoise

Zhenghao Lin, Yeyun Gong, Yelong Shen, Tong Wu, Zhihao Fan

Simplifying Momentum-based Positive-definite Submanifold Optimization with Applications to Deep Learning

Wu Lin, Valentin Duruisseaux, Melvin Leok, Frank Nielsen, Mohammad Emtiyaz Khan

Hyperbolic Diffusion Embedding and Distance for Hierarchical Representation Learning

Ya-Wei Eileen Lin, Ronald R. Coifman, Gal Mishne, Ronen Talmon

Generating Novel, Designable, and Diverse Protein Structures by Equivariantly Diffusing Oriented Residue Clouds

Yeqing Lin, Mohammed AlQuraishi

Variational Open-Domain Question Answering

Valentin Liévin, Andreas Geert Motzfeldt, Ida Riis Jensen, Ole Winther

Revisiting Domain Randomization via Relaxed State-Adversarial Policy Optimization

Yun-Hsuan Lien, Ping-Chun Hsieh, Yu-Shuen Wang

Supervised Metric Learning to Rank for Retrieval via Contextual Similarity Optimization

Christopher Liao, Theodoros Tsiligkaridis, Brian Kulis

Statistical Inference and A/B Testing for First-Price Pacing Equilibria

Luofeng Liao, Christian Kroer

Less is More: Task-aware Layer-wise Distillation for Language Model Compression

Chen Liang, Simiao Zuo, Qingru Zhang, Pengcheng He, Weizhu Chen

Conformal Inference is (almost) Free for Neural Networks Trained with Early Stopping

Ziyi Liang, Yanfei Zhou, Matteo Sesia

CLUSTSEG: Clustering for Universal Segmentation

James Chenhao Liang, Tianfei Zhou, Dongfang Liu, Wenguan Wang

Adversarial Example Does Good: Preventing Painting Imitation from Diffusion Models via Adversarial Examples

Chumeng Liang, Xiaoyu Wu, Yang Hua, Jiaru Zhang, Yiming Xue

Learning Compiler Pass Orders using Coreset and Normalized Value Prediction

Youwei Liang, Kevin Stone, Ali Shameli, Chris Cummins, Mostafa Elhoushi

AdaptDiffuser: Diffusion Models as Adaptive Self-evolving Planners

Zhixuan Liang, Yao Mu, Mingyu Ding, Fei Ni, Masayoshi Tomizuka

Accuracy on the Curve: On the Nonlinear Correlation of ML Performance Between Data Subpopulations

Weixin Liang, Yining Mao, Yongchan Kwon, Xinyu Yang, James Zou

A Distribution Optimization Framework for Confidence Bounds of Risk Measures

Hao Liang, Zhi-Quan Luo

Consistency of Multiple Kernel Clustering

Weixuan Liang, Xinwang Liu, Yong Liu, Chuan Ma, Yunping Zhao

Low Complexity Homeomorphic Projection to Ensure Neural-Network Solution Feasibility for Optimization over (Non-)Convex Set

Enming Liang, Minghua Chen, Steven Low

Structured Cooperative Learning with Graphical Model Priors

Shuangtong Li, Tianyi Zhou, Xinmei Tian, Dacheng Tao

Trustworthy Policy Learning under the Counterfactual No-Harm Criterion

Haoxuan Li, Chunyuan Zheng, Yixiao Cao, Zhi Geng, Yue Liu

Internally Rewarded Reinforcement Learning

Mengdi Li, Xufeng Zhao, Jae Hee Lee, Cornelius Weber, Stefan Wermter

Optimal Arms Identification with Knapsacks

Shaoang Li, Lan Zhang, Yingqi Yu, Xiangyang Li

Offline Reinforcement Learning with Closed-Form Policy Improvement Operators

Jiachen Li, Edwin Zhang, Ming Yin, Qinxun Bai, Yu-Xiang Wang

Cooperative Open-ended Learning Framework for Zero-Shot Coordination

Yang Li, Shao Zhang, Jichen Sun, Yali Du, Ying Wen

Does a Neural Network Really Encode Symbolic Concepts?

Mingjie Li, Quanshi Zhang

Understanding the Complexity Gains of Single-Task RL with a Curriculum

Qiyang Li, Yuexiang Zhai, Yi Ma, Sergey Levine

Alternating Local Enumeration (TnALE): Solving Tensor Network Structure Search with Fewer Evaluations

CHAO LI, Junhua Zeng, Chunmei Li, Cesar F Caiafa, Qibin Zhao

Nesterov Meets Optimism: Rate-Optimal Separable Minimax Optimization

Chris Junchi Li, Huizhuo Yuan, Gauthier Gidel, Quanquan Gu, Michael Jordan

LoSparse: Structured Compression of Large Language Models based on Low-Rank and Sparse Approximation

Yixiao Li, Yifan Yu, Qingru Zhang, Chen Liang, Pengcheng He

Achieving Hierarchy-Free Approximation for Bilevel Programs with Equilibrium Constraints

Jiayang Li, Jing Yu, Boyi Liu, Yu Nie, Zhaoran Wang

FedVS: Straggler-Resilient and Privacy-Preserving Vertical Federated Learning for Split Models

Songze Li, Duanyi Yao, Jin Liu

Learning for Edge-Weighted Online Bipartite Matching with Robustness Guarantees

Pengfei Li, Jianyi Yang, Shaolei Ren

Transcendental Idealism of Planner: Evaluating Perception from Planning Perspective for Autonomous Driving

Weixin Li, Xiaodong Yang

Horizon-free Learning for Markov Decision Processes and Games: Stochastically Bounded Rewards and Improved Bounds

Shengshi Li, Lin Yang

SMURF-THP: Score Matching-based UnceRtainty quantiFication for Transformer Hawkes Process

Zichong Li, Yanbo Xu, Simiao Zuo, Haoming Jiang, Chao Zhang

GraphCleaner: Detecting Mislabelled Samples in Popular Graph Learning Benchmarks

Yuwen Li, Miao Xiong, Bryan Hooi

Propensity Matters: Measuring and Enhancing Balancing for Recommendation

Haoxuan Li, Yanghao Xiao, Chunyuan Zheng, Peng Wu, Peng Cui

Learning Antidote Data to Individual Unfairness

Peizhao Li, Ethan Xia, Hongfu Liu

Architecture-Agnostic Masked Image Modeling -- From ViT back to CNN

Siyuan Li, Di Wu, Fang Wu, Zelin Zang, Stan Z. Li