Chen, Yuxin

113 publications

NeurIPS 2025 Adaptive Divergence Regularized Policy Optimization for Fine-Tuning Generative Models Jiajun Fan, Tong Wei, Chaoran Cheng, Yuxin Chen, Ge Liu

COLT 2025 Anytime Acceleration of Gradient Descent Zihan Zhang, Jason Lee, Simon Du, Yuxin Chen

UAI 2025 Bayesian Optimization with Inexact Acquisition: Is Random Grid Search Sufficient? Hwanwoo Kim, Chong Liu, Yuxin Chen

AISTATS 2025 Constrained Multi-Objective Bayesian Optimization Through Optimistic Constraints Estimation Diantong Li, Fengxue Zhang, Chong Liu, Yuxin Chen

ICCV 2025 DOGR: Towards Versatile Visual Document Grounding and Referring Yinan Zhou, Yuxin Chen, Haokun Lin, Yichen Wu, Shuyu Yang, Zhongang Qi, Chen Ma, Li Zhu

NeurIPS 2025 Deployment Efficient Reward-Free Exploration with Linear Function Approximation Zihan Zhang, Yuxin Chen, Jason D. Lee, Simon Shaolei Du, Lin Yang, Ruosong Wang

AAAI 2025 Designing Specialized Two-Dimensional Graph Spectral Filters for Spatial-Temporal Graph Modeling Yuxin Chen, Fangru Lin, Jingyi Huo, Hui Yan

NeurIPS 2025 EditInfinity: Image Editing with Binary-Quantized Generative Models Jiahuan Wang, Yuxin Chen, Jun Yu, Guangming Lu, Wenjie Pei

UAI 2025 Finding Interior Optimum of Black-Box Constrained Objective with Bayesian Optimization Fengxue Zhang, Yuxin Chen

NeurIPS 2025 Formal Models of Active Learning from Contrastive Examples Farnam Mansouri, Hans U. Simon, Adish Singla, Yuxin Chen, Sandra Zilles

ICLR 2025 Language Representations Can Be What Recommenders Need: Findings and Potentials Leheng Sheng, An Zhang, Yi Zhang, Yuxin Chen, Xiang Wang, Tat-Seng Chua

COLT 2025 Low-Dimensional Adaptation of Diffusion Models: Convergence in Total Variation (extended Abstract) Jiadong Liang, Zhihan Huang, Yuxin Chen

CoRL 2025 MEReQ: Max-Ent Residual-Q Inverse RL for Sample-Efficient Alignment from Intervention Yuxin Chen, Chen Tang, Jianglan Wei, Chenran Li, Thomas Tian, Xiang Zhang, Wei Zhan, Peter Stone, Masayoshi Tomizuka

ICCV 2025 Mamba-3VL: Taming State Space Model for 3D Vision Language Learning Yuan Wang, Yuxin Chen, Zhongang Qi, Lijun Liu, Jile Jiao, Xuetao Feng, Yujia Liang, Ying Shan, Zhipeng Zhang

NeurIPS 2025 MindOmni: Unleashing Reasoning Generation in Vision Language Models with RGPO Yicheng Xiao, Lin Song, Yukang Chen, Yingmin Luo, Yuxin Chen, Yukang Gan, Wei Huang, Xiu Li, Xiaojuan Qi, Ying Shan

ICML 2025 Minimax Optimal Regret Bound for Reinforcement Learning with Trajectory Feedback Zihan Zhang, Yuxin Chen, Jason D. Lee, Simon Shaolei Du, Ruosong Wang

CVPR 2025 Mono2Stereo: A Benchmark and Empirical Study for Stereo Conversion Songsong Yu, Yuxin Chen, Zhongang Qi, Zeke Xie, Yifan Wang, Lijun Wang, Ying Shan, Huchuan Lu

ICLR 2025 Online Reward-Weighted Fine-Tuning of Flow Matching with Wasserstein Regularization Jiajun Fan, Shuaike Shen, Chaoran Cheng, Yuxin Chen, Chumeng Liang, Ge Liu

NeurIPS 2025 Riemannian Consistency Model Chaoran Cheng, Yusong Wang, Yuxin Chen, Xiangxin Zhou, Nanning Zheng, Ge Liu

AISTATS 2025 Robust Multi-Fidelity Bayesian Optimization with Deep Kernel and Partition Fengxue Zhang, Thomas Desautels, Yuxin Chen

ICML 2025 Taming Rectified Flow for Inversion and Editing Jiangshan Wang, Junfu Pu, Zhongang Qi, Jiayi Guo, Yue Ma, Nisha Huang, Yuxin Chen, Xiu Li, Ying Shan

NeurIPS 2025 The Emergence of Abstract Thought in Large Language Models Beyond Any Language Yuxin Chen, Yiran Zhao, Yang Zhang, An Zhang, Kenji Kawaguchi, Shafiq Joty, Junnan Li, Tat-Seng Chua, Michael Qizhe Shieh, Wenxuan Zhang

NeurIPS 2025 Transformers Provably Learn Chain-of-Thought Reasoning with Length Generalization Yu Huang, Zixin Wen, Aarti Singh, Yuejie Chi, Yuxin Chen

CoRL 2025 Versatile Loco-Manipulation Through Flexible Interlimb Coordination Xinghao Zhu, Yuxin Chen, Lingfeng Sun, Farzad Niroui, Simon Le Cleac’h, Jiuguang Wang, Kuan Fang

ICCV 2025 VisionMath: Vision-Form Mathematical Problem-Solving Zongyang Ma, Yuxin Chen, Ziqi Zhang, Zhongang Qi, Chunfeng Yuan, Shaojie Zhu, Chengxiang Zhuo, Bing Li, Ye Liu, Zang Li, Ying Shan, Weiming Hu

ICML 2024 Accelerating Convergence of Score-Based Diffusion Models, Provably Gen Li, Yu Huang, Timofey Efimov, Yuting Wei, Yuejie Chi, Yuxin Chen

NeurIPSW 2024 Active Learning for Optimal Minimization of Experimental Characterization Uncertainty Marcus Schwarting, Nathan Seifert, Logan Ward, Ben Blaiszik, Ian Foster, Yuxin Chen, Kirill Prozument

NeurIPS 2024 Advancing Cross-Domain Discriminability in Continual Learning of Vision-Language Models Yicheng Xu, Yuxin Chen, Jiahao Nie, Yusong Wang, Huiping Zhuang, Manabu Okumura

ICLR 2024 Beyond Reverse KL: Generalizing Direct Preference Optimization with Diverse Divergence Constraints Chaoqi Wang, Yibo Jiang, Chenghao Yang, Han Liu, Yuxin Chen

ICLR 2024 Blending Imitation and Reinforcement Learning for Robust Policy Improvement Xuefeng Liu, Takuma Yoneda, Rick Stevens, Matthew Walter, Yuxin Chen

NeurIPSW 2024 Constrained Multi-Objective Bayesian Optimization Diantong Li, Fengxue Zhang, Chong Liu, Yuxin Chen

NeurIPS 2024 Contextual Active Model Selection Xuefeng Liu, Fangfang Xia, Rick L. Stevens, Yuxin Chen

NeurIPSW 2024 Direct Acquisition Optimization for Low-Budget Active Learning Zhuokai Zhao, Yibo Jiang, Yuxin Chen

AISTATS 2024 Don’t Be Pessimistic Too Early: Look K Steps Ahead! Chaoqi Wang, Ziyu Ye, Kevin Murphy, Yuxin Chen

ECCV 2024 EA-VTR: Event-Aware Video-Text Retrieval Zongyang Ma, Ziqi Zhang, Yuxin Chen, Zhongang Qi, Chunfeng Yuan, Bing Li, Yingmin Luo, Xu Li, Xiaojuan Qi, Ying Shan, Weiming Hu

ICLR 2024 Enhancing Instance-Level Image Classification with Set-Level Labels Renyu Zhang, Aly A Khan, Yuxin Chen, Robert L. Grossman

NeurIPS 2024 Federated Natural Policy Gradient and Actor Critic Methods for Multi-Task Reinforcement Learning Tong Yang, Shicong Cen, Yuting Wei, Yuxin Chen, Yuejie Chi

NeurIPSW 2024 Finding Interior Optimum of Black-Box Constrained Objective with Bayesian Optimization Fengxue Zhang, Zejie Zhu, Yuxin Chen

NeurIPS 2024 GTSinger: A Global Multi-Technique Singing Corpus with Realistic Music Scores for All Singing Tasks Yu Zhang, Changhao Pan, Wenxiang Guo, Ruiqi Li, Zhiyuan Zhu, Jialei Wang, Wenhao Xu, Jingyu Lu, Zhiqing Hong, Chuxin Wang, LiChao Zhang, Jinzheng He, Ziyue Jiang, Yuxin Chen, Chen Yang, Jiecheng Zhou, Xinyu Cheng, Zhou Zhao

ICLR 2024 Horizon-Free Regret for Linear Markov Decision Processes Zihan Zhang, Jason D. Lee, Yuxin Chen, Simon Shaolei Du

CVPR 2024 How to Make Cross Encoder a Good Teacher for Efficient Image-Text Retrieval? Yuxin Chen, Zongyang Ma, Ziqi Zhang, Zhongang Qi, Chunfeng Yuan, Bing Li, Junfu Pu, Ying Shan, Xiaojuan Qi, Weiming Hu

UAI 2024 Learning to Rank for Active Learning via Multi-Task Bilevel Optimization Zixin Ding, Si Chen, Ruoxi Jia, Yuxin Chen

COLT 2024 Minimax-Optimal Reward-Agnostic Exploration in Reinforcement Learning Gen Li, Yuling Yan, Yuxin Chen, Jianqing Fan

AISTATS 2024 Model-Based Policy Optimization Under Approximate Bayesian Inference Chaoqi Wang, Yuxin Chen, Kevin Murphy

UAI 2024 No-Regret Learning of Nash Equilibrium for Black-Box Games via Gaussian Processes Minbiao Han, Fengxue Zhang, Yuxin Chen

NeurIPS 2024 On SoftMax Direct Preference Optimization for Recommendation Yuxin Chen, Junfei Tan, An Zhang, Zhengyi Yang, Leheng Sheng, Enzhi Zhang, Xiang Wang, Tat-Seng Chua

COLT 2024 Optimal Multi-Distribution Learning Zihan Zhang, Wenhao Zhan, Yuxin Chen, Simon S Du, Jason D Lee

NeurIPSW 2024 Reasoning in Reasoning: A Hierarchical Framework for Better and Faster Neural Theorem Proving Ziyu Ye, Jiacheng Chen, Jonathan Light, Yifei Wang, Jiankai Sun, Mac Schwager, Philip Torr, Guohao Li, Yuxin Chen, Kaiyu Yang, Yisong Yue, Ziniu Hu

NeurIPSW 2024 Robust Multi-Fidelity Bayesian Optimization with Deep Kernel and Partition Fengxue Zhang, Thomas Desautels, Yuxin Chen

COLT 2024 Settling the Sample Complexity of Online Reinforcement Learning Zihan Zhang, Yuxin Chen, Jason D Lee, Simon S Du

ICLR 2024 Towards Non-Asymptotic Convergence for Diffusion-Based Generative Models Gen Li, Yuting Wei, Yuxin Chen, Yuejie Chi

ICML 2024 Transformers Implement Functional Gradient Descent to Learn Non-Linear Functions in Context Xiang Cheng, Yuxin Chen, Suvrit Sra

ICML 2024 Wukong: Towards a Scaling Law for Large-Scale Recommendation Buyun Zhang, Liang Luo, Yuxin Chen, Jade Nie, Xi Liu, Shen Li, Yanli Zhao, Yuchen Hao, Yantao Yao, Ellie Dingqiao Wen, Jongsoo Park, Maxim Naumov, Wenlin Chen

ICML 2023 Active Policy Improvement from Multiple Black-Box Oracles Xuefeng Liu, Takuma Yoneda, Chaoqi Wang, Matthew Walter, Yuxin Chen

NeurIPSW 2023 Beyond Reverse KL: Generalizing Direct Preference Optimization with Diverse Divergence Constraints Chaoqi Wang, Yibo Jiang, Chenghao Yang, Han Liu, Yuxin Chen

NeurIPSW 2023 Beyond Reverse KL: Generalizing Direct Preference Optimization with Diverse Divergence Constraints Chaoqi Wang, Yibo Jiang, Chenghao Yang, Han Liu, Yuxin Chen

IJCAI 2023 Efficient Online Decision Tree Learning with Active Feature Acquisition Arman Rahbar, Ziyu Ye, Yuxin Chen, Morteza Haghir Chehreghani

ICMLW 2023 Iterative Machine Teaching for Black-Box Markov Learners Chaoqi Wang, Sandra Zilles, Adish Singla, Yuxin Chen

ICLR 2023 Learning Human-Compatible Representations for Case-Based Decision Support Han Liu, Yizhou Tian, Chacha Chen, Shi Feng, Yuxin Chen, Chenhao Tan

ICML 2023 Learning Regions of Interest for Bayesian Optimization with Adaptive Level-Set Estimation Fengxue Zhang, Jialin Song, James C Bowden, Alexander Ladd, Yisong Yue, Thomas Desautels, Yuxin Chen

ICMLW 2023 Model-Based Policy Optimization Under Approximate Bayesian Inference Chaoqi Wang, Yuxin Chen, Kevin Patrick Murphy

ICCV 2023 Order-Prompted Tag Sequence Generation for Video Tagging Zongyang Ma, Ziqi Zhang, Yuxin Chen, Zhongang Qi, Yingmin Luo, Zekun Li, Chunfeng Yuan, Bing Li, Xiaohu Qie, Ying Shan, Weiming Hu

NeurIPS 2023 Reward-Agnostic Fine-Tuning: Provable Statistical Benefits of Hybrid Reinforcement Learning Gen Li, Wenhao Zhan, Jason Lee, Yuejie Chi, Yuxin Chen

ICLR 2023 Scalable Batch-Mode Deep Bayesian Active Learning via Equivalence Class Annealing Renyu Zhang, Aly A Khan, Robert L. Grossman, Yuxin Chen

NeurIPS 2023 The Curious Price of Distributional Robustness in Reinforcement Learning with a Generative Model Laixi Shi, Gen Li, Yuting Wei, Yuxin Chen, Matthieu Geist, Yuejie Chi

CVPR 2023 ViLEM: Visual-Language Error Modeling for Image-Text Retrieval Yuxin Chen, Zongyang Ma, Ziqi Zhang, Zhongang Qi, Chunfeng Yuan, Ying Shan, Bing Li, Weiming Hu, Xiaohu Qie, Jianping Wu

CVPRW 2022 Class-Wise Thresholding for Robust Out-of-Distribution Detection Matteo Guarrera, Baihong Jin, Tung-Wei Lin, Maria A. Zuluaga, Yuxin Chen, Alberto L. Sangiovanni-Vincentelli

NeurIPS 2022 Minimax-Optimal Multi-Agent RL in Markov Games with a Generative Model Gen Li, Yuejie Chi, Yuting Wei, Yuxin Chen

CVPR 2022 Open-Vocabulary One-Stage Detection with Hierarchical Visual-Language Knowledge Distillation Zongyang Ma, Guan Luo, Jin Gao, Liang Li, Yuxin Chen, Shaoru Wang, Congxuan Zhang, Weiming Hu

ICML 2022 Pessimistic Q-Learning for Offline Reinforcement Learning: Towards Optimal Sample Complexity Laixi Shi, Gen Li, Yuting Wei, Yuxin Chen, Yuejie Chi

AISTATS 2021 The Teaching Dimension of Kernel Perceptron Akash Kumar, Hanqi Zhang, Adish Singla, Yuxin Chen

AAAI 2021 Adaptive Teaching of Temporal Logic Formulas to Preference-Based Learners Zhe Xu, Yuxin Chen, Ufuk Topcu

NeurIPS 2021 Breaking the Sample Complexity Barrier to Regret-Optimal Model-Free Reinforcement Learning Gen Li, Laixi Shi, Yuxin Chen, Yuantao Gu, Yuejie Chi

ICCV 2021 Channel-Wise Topology Refinement Graph Convolution for Skeleton-Based Action Recognition Yuxin Chen, Ziqi Zhang, Chunfeng Yuan, Bing Li, Ying Deng, Weiming Hu

ICLR 2021 Learning to Make Decisions via Submodular Regularization Ayya Alieva, Aiden Aceves, Jialin Song, Stephen Mayo, Yisong Yue, Yuxin Chen

NeurIPS 2021 Sample-Efficient Reinforcement Learning Is Feasible for Linearly Realizable MDPs with Limited Revisiting Gen Li, Yuxin Chen, Yuejie Chi, Yuantao Gu, Yuting Wei

COLT 2021 SoftMax Policy Gradient Methods Can Take Exponential Time to Converge Gen Li, Yuting Wei, Yuejie Chi, Yuantao Gu, Yuxin Chen

FnTML 2021 Spectral Methods for Data Science: A Statistical Perspective Yuxin Chen, Yuejie Chi, Jianqing Fan, Cong Ma

NeurIPS 2021 Teaching an Active Learner with Contrastive Examples Chaoqi Wang, Adish Singla, Yuxin Chen

NeurIPS 2021 Teaching via Best-Case Counterexamples in the Learning-with-Equivalence-Queries Paradigm Akash Kumar, Yuxin Chen, Adish Singla

ICML 2021 Tightening the Dependence on Horizon in the Sample Complexity of Q-Learning Gen Li, Changxiao Cai, Yuxin Chen, Yuantao Gu, Yuting Wei, Yuejie Chi

IJCAI 2021 Understanding the Effect of Bias in Deep Anomaly Detection Ziyu Ye, Yuxin Chen, Haitao Zheng

IJCAI 2020 An Online Learning Framework for Energy-Efficient Navigation of Electric Vehicles Niklas Åkerblom, Yuxin Chen, Morteza Haghir Chehreghani

NeurIPS 2020 Breaking the Sample Size Barrier in Model-Based Reinforcement Learning with a Generative Model Gen Li, Yuting Wei, Yuejie Chi, Yuantao Gu, Yuxin Chen

AISTATS 2020 Communication-Efficient Distributed Optimization in Networks with Gradient Tracking and Variance Reduction Boyue Li, Shicong Cen, Yuxin Chen, Yuejie Chi

JMLR 2020 Communication-Efficient Distributed Optimization in Networks with Gradient Tracking and Variance Reduction Boyue Li, Shicong Cen, Yuxin Chen, Yuejie Chi

NeurIPS 2020 Sample Complexity of Asynchronous Q-Learning: Sharper Analysis and Variance Reduction Gen Li, Yuting Wei, Yuejie Chi, Yuantao Gu, Yuxin Chen

ICML 2020 Uncertainty Quantification for Nonconvex Tensor Completion: Confidence Intervals, Heteroscedasticity and Optimality Changxiao Cai, H. Vincent Poor, Yuxin Chen

IJCAI 2020 Understanding the Power and Limitations of Teaching with Imperfect Knowledge Rati Devidze, Farnam Mansouri, Luis Haug, Yuxin Chen, Adish Singla

AISTATS 2019 A General Framework for Multi-Fidelity Bayesian Optimization with Gaussian Processes Jialin Song, Yuxin Chen, Yisong Yue

AISTATS 2019 Batched Stochastic Bayesian Optimization via Combinatorial Constraints Design Kevin K. Yang, Yuxin Chen, Alycia Lee, Yisong Yue

NeurIPS 2019 Landmark Ordinal Embedding Nikhil Ghosh, Yuxin Chen, Yisong Yue

NeurIPS 2019 Nonconvex Low-Rank Tensor Completion from Noisy Data Changxiao Cai, Gen Li, H. Vincent Poor, Yuxin Chen

AISTATS 2019 Nonconvex Matrix Factorization from Rank-One Measurements Yuanxin Li, Cong Ma, Yuxin Chen, Yuejie Chi

NeurIPS 2019 Preference-Based Batch and Sequential Teaching: Towards a Unified View of Models Farnam Mansouri, Yuxin Chen, Ara Vartanian, Xiaojin Zhu, Adish Singla

NeurIPS 2019 Teaching Multiple Concepts to a Forgetful Learner Anette Hunziker, Yuxin Chen, Oisin Mac Aodha, Manuel Gomez Rodriguez, Andreas Krause, Pietro Perona, Yisong Yue, Adish Singla

AAAI 2019 Type Sequence Preserving Heterogeneous Information Network Embedding Yuxin Chen, Tengjiao Wang, Wei Chen, Qiang Li, Zhen Qiu

ICML 2018 Implicit Regularization in Nonconvex Statistical Estimation: Gradient Descent Converges Linearly for Phase Retrieval and Matrix Completion Cong Ma, Kaizheng Wang, Yuejie Chi, Yuxin Chen

AISTATS 2018 Near-Optimal Machine Teaching via Explanatory Teaching Sets Yuxin Chen, Oisin Mac Aodha, Shihan Su, Pietro Perona, Yisong Yue

NeurIPS 2018 Understanding the Role of Adaptivity in Machine Teaching: The Case of Version Space Learners Yuxin Chen, Adish Singla, Oisin Mac Aodha, Pietro Perona, Yisong Yue

UAI 2017 Efficient Online Learning for Optimizing Value of Information: Theory and Application to Interactive Troubleshooting Yuxin Chen, Jean-Michel Renders, Morteza Haghir Chehreghani, Andreas Krause

AISTATS 2017 Near-Optimal Bayesian Active Learning with Correlated and Noisy Tests Yuxin Chen, Seyed Hamed Hassani, Andreas Krause

ICML 2016 Community Recovery in Graphs with Locality Yuxin Chen, Govinda Kamath, Changho Suh, David Tse

COLT 2015 Sequential Information Maximization: When Is Greedy Near-Optimal? Yuxin Chen, S. Hamed Hassani, Amin Karbasi, Andreas Krause

NeurIPS 2015 Solving Random Quadratic Systems of Equations Is Nearly as Easy as Solving Linear Systems Yuxin Chen, Emmanuel Candes

ICML 2015 Spectral MLE: Top-K Rank Aggregation from Pairwise Comparisons Yuxin Chen, Changho Suh

AAAI 2015 Submodular Surrogates for Value of Information Yuxin Chen, Shervin Javdani, Amin Karbasi, J. Andrew Bagnell, Siddhartha S. Srinivasa, Andreas Krause

ICML 2014 Active Detection via Adaptive Submodularity Yuxin Chen, Hiroaki Shioi, Cesar Fuentes Montesinos, Lian Pin Koh, Serge Wich, Andreas Krause

AISTATS 2014 Near Optimal Bayesian Active Learning for Decision Making Shervin Javdani, Yuxin Chen, Amin Karbasi, Andreas Krause, Drew Bagnell, Siddhartha S. Srinivasa

ICML 2014 Near-Optimal Joint Object Matching via Convex Relaxation Yuxin Chen, Leonidas Guibas, Qixing Huang

ICML 2014 Scalable Semidefinite Relaxation for Maximum a Posterior Estimation Qixing Huang, Yuxin Chen, Leonidas Guibas

ICML 2013 Near-Optimal Batch Mode Active Learning and Adaptive Submodular Optimization Yuxin Chen, Andreas Krause

ICML 2013 Spectral Compressed Sensing via Structured Matrix Completion Yuxin Chen, Yuejie Chi