Cong Shen

A Shared Low-Rank Adaptation Approach to Personalized RLHF AISTATS 2025 Augmenting Online RL with Offline Data is All You Need: A Unified Hybrid RL Algorithm Design and Analysis UAI 2025 Cost-Aware Optimal Pairwise Pure Exploration AISTATS 2025 Data-adaptive Differentially Private Prompt Synthesis for In-Context Learning ICLR 2025 DCT-Net: Dual-branch CT Reconstruction from Orthogonal X-rays with Diffusion Model and Contrastive Learning MICCAI 2025 From Cross-Task Examples to In-Task Prompts: A Graph-Based Pseudo-Labeling Framework for In-context Learning EMNLP 2025 MAPLE: Many-Shot Adaptive Pseudo-Labeling for In-Context Learning ICML 2025 On the Learn-to-Optimize Capabilities of Transformers in In-Context Sparse Recovery ICLR 2025 On the Training Convergence of Transformers for In-Context Classification of Gaussian Mixtures ICML 2025 Separate the Wheat from the Chaff: Winnowing Down Divergent Views in Retrieval Augmented Generation EMNLP 2025 Efficient Prompt Optimization Through the Lens of Best Arm Identification NeurIPS 2024 FastGAS: Fast Graph-based Annotation Selection for In-Context Learning ACL 2024 Federated Representation Learning in the Under-Parameterized Regime ICML 2024 Mixture of Demonstrations for In-Context Learning NeurIPS 2024 Stochastic Smoothed Gradient Descent Ascent for Federated Minimax Optimization AISTATS 2024 Transformers as Game Players: Provable In-context Game-playing Capabilities of Pre-trained Models NeurIPS 2024 Verification of Machine Unlearning is Fragile ICML 2024 Federated Linear Bandits with Finite Adversarial Actions NeurIPS 2023 Nearly Minimax Optimal Offline Reinforcement Learning with Linear Function Approximation: Single-Agent MDP and Markov Game ICLR 2023 Near-optimal Conservative Exploration in Reinforcement Learning under Episode-wise Constraints ICML 2023 Provably Efficient Offline Reinforcement Learning with Perturbed Data Sources ICML 2023 A Self-Play Posterior Sampling Algorithm for Zero-Sum Markov Games ICML 2022 (Almost) Free Incentivized Exploration from Decentralized Learning Agents NeurIPS 2021 Federated Linear Contextual Bandits NeurIPS 2021 Federated Multi-Armed Bandits AAAI 2021 Federated Multi-armed Bandits with Personalization AISTATS 2021 Heterogeneous Multi-player Multi-armed Bandits: Closing the Gap and Generalization NeurIPS 2021 SDF-Bayes: Cautious Optimism in Safe Dose-Finding Clinical Trials with Drug Combinations and Heterogeneous Patient Groups AISTATS 2021 Contextual Constrained Learning for Dose-Finding Clinical Trials AISTATS 2020 Decentralized Multi-player Multi-armed Bandits with No Collision Information AISTATS 2020 Learning for Dose Allocation in Adaptive Clinical Trials with Safety Constraints ICML 2020 Robust Recursive Partitioning for Heterogeneous Treatment Effects with Uncertainty Quantification NeurIPS 2020 Stochastic Linear Contextual Bandits with Diverse Contexts AISTATS 2020 Cost-aware Cascading Bandits IJCAI 2018 Regional Multi-Armed Bandits AISTATS 2018