Shen, Cong

37 publications

AISTATS 2025 A Shared Low-Rank Adaptation Approach to Personalized RLHF Renpu Liu, Peng Wang, Donghao Li, Cong Shen, Jing Yang

NeurIPS 2025 A Single-Loop First-Order Algorithm for Linearly Constrained Bilevel Optimization Wei Shen, Jiawei Zhang, Minhui Huang, Cong Shen

UAI 2025 Augmenting Online RL with Offline Data Is All You Need: A Unified Hybrid RL Algorithm Design and Analysis Ruiquan Huang, Donghao Li, Chengshuai Shi, Cong Shen, Jing Yang

AISTATS 2025 Cost-Aware Optimal Pairwise Pure Exploration Di Wu, Chengshuai Shi, Ruida Zhou, Cong Shen

ICLR 2025 Data-Adaptive Differentially Private Prompt Synthesis for In-Context Learning Fengyu Gao, Ruida Zhou, Tianhao Wang, Cong Shen, Jing Yang

TMLR 2025 FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Zihan Chen, Xingbo Fu, Yushun Dong, Jundong Li, Cong Shen

NeurIPS 2025 Greedy Sampling Is Provably Efficient for RLHF Di Wu, Chengshuai Shi, Jing Yang, Cong Shen

ICML 2025 MAPLE: Many-Shot Adaptive Pseudo-Labeling for In-Context Learning Zihan Chen, Song Wang, Zhen Tan, Jundong Li, Cong Shen

ICLR 2025 On the Learn-to-Optimize Capabilities of Transformers in In-Context Sparse Recovery Renpu Liu, Ruida Zhou, Cong Shen, Jing Yang

ICML 2025 On the Training Convergence of Transformers for In-Context Classification of Gaussian Mixtures Wei Shen, Ruida Zhou, Jing Yang, Cong Shen

NeurIPS 2024 Efficient Prompt Optimization Through the Lens of Best Arm Identification Chengshuai Shi, Kun Yang, Zihan Chen, Jundong Li, Jing Yang, Cong Shen

ICML 2024 Federated Representation Learning in the Under-Parameterized Regime Renpu Liu, Cong Shen, Jing Yang

TMLR 2024 Harnessing the Power of Federated Learning in Federated Contextual Bandits Chengshuai Shi, Ruida Zhou, Kun Yang, Cong Shen

NeurIPS 2024 Mixture of Demonstrations for In-Context Learning Song Wang, Zihan Chen, Chengshuai Shi, Cong Shen, Jundong Li

AISTATS 2024 Stochastic Smoothed Gradient Descent Ascent for Federated Minimax Optimization Wei Shen, Minhui Huang, Jiawei Zhang, Cong Shen

NeurIPS 2024 Transformers as Game Players: Provable In-Context Game-Playing Capabilities of Pre-Trained Models Chengshuai Shi, Kun Yang, Jing Yang, Cong Shen

ICML 2024 Verification of Machine Unlearning Is Fragile Binchi Zhang, Zihan Chen, Cong Shen, Jundong Li

NeurIPS 2023 Federated Linear Bandits with Finite Adversarial Actions Li Fan, Ruida Zhou, Chao Tian, Cong Shen

NeurIPSW 2023 Harnessing the Power of Federated Learning in Federated Contextual Bandits Chengshuai Shi, Kun Yang, Ruida Zhou, Cong Shen

ICML 2023 Near-Optimal Conservative Exploration in Reinforcement Learning Under Episode-Wise Constraints Donghao Li, Ruiquan Huang, Cong Shen, Jing Yang

ICLR 2023 Nearly Minimax Optimal Offline Reinforcement Learning with Linear Function Approximation: Single-Agent MDP and Markov Game Wei Xiong, Han Zhong, Chengshuai Shi, Cong Shen, Liwei Wang, Tong Zhang

ICML 2023 Provably Efficient Offline Reinforcement Learning with Perturbed Data Sources Chengshuai Shi, Wei Xiong, Cong Shen, Jing Yang

ICML 2022 A Self-Play Posterior Sampling Algorithm for Zero-Sum Markov Games Wei Xiong, Han Zhong, Chengshuai Shi, Cong Shen, Tong Zhang

ICLRW 2022 A Self-Play Posterior Sampling Algorithm for Zero-Sum Markov Games Wei Xiong, Han Zhong, Chengshuai Shi, Cong Shen, Tong Zhang

AISTATS 2021 Federated Multi-Armed Bandits with Personalization Chengshuai Shi, Cong Shen, Jing Yang

AISTATS 2021 SDF-Bayes: Cautious Optimism in Safe Dose-Finding Clinical Trials with Drug Combinations and Heterogeneous Patient Groups Hyun-Suk Lee, Cong Shen, William Zame, Jang-Won Lee, Mihaela Schaar

NeurIPS 2021 (Almost) Free Incentivized Exploration from Decentralized Learning Agents Chengshuai Shi, Haifeng Xu, Wei Xiong, Cong Shen

NeurIPS 2021 Federated Linear Contextual Bandits Ruiquan Huang, Weiqiang Wu, Jing Yang, Cong Shen

AAAI 2021 Federated Multi-Armed Bandits Chengshuai Shi, Cong Shen

NeurIPS 2021 Heterogeneous Multi-Player Multi-Armed Bandits: Closing the Gap and Generalization Chengshuai Shi, Wei Xiong, Cong Shen, Jing Yang

AISTATS 2020 Contextual Constrained Learning for Dose-Finding Clinical Trials Hyun-Suk Lee, Cong Shen, James Jordon, Mihaela Schaar

AISTATS 2020 Decentralized Multi-Player Multi-Armed Bandits with No Collision Information Chengshuai Shi, Wei Xiong, Cong Shen, Jing Yang

ICML 2020 Learning for Dose Allocation in Adaptive Clinical Trials with Safety Constraints Cong Shen, Zhiyang Wang, Sofia Villar, Mihaela Van Der Schaar

NeurIPS 2020 Robust Recursive Partitioning for Heterogeneous Treatment Effects with Uncertainty Quantification Hyun-Suk Lee, Yao Zhang, William Zame, Cong Shen, Jang-Won Lee, Mihaela van der Schaar

AISTATS 2020 Stochastic Linear Contextual Bandits with Diverse Contexts Weiqiang Wu, Jing Yang, Cong Shen

IJCAI 2018 Cost-Aware Cascading Bandits Ruida Zhou, Chao Gan, Jing Yang, Cong Shen

AISTATS 2018 Regional Multi-Armed Bandits Zhiyang Wang, Ruida Zhou, Cong Shen