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Research Interest My recent research interest generally focuses on solving sequential decision-making problems, which lies at the intersection of reinforcement learning, game theory, optimization, and statistical learning. In addition, I am also interested in the application of machine learning to the various areas such as large language models, econometrics, computer vision, and data mining.
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Selected Recent Publication [Full List]
Rewards-in-Context: Multi-Objective Alignment of Foundation
Models with Dynamic Preference Adjustment
Preprint [PDF] [Codes] Pessimism Meets Risk: Risk-Sensitive Offline Reinforcement Learning Preprint Posterior Sampling for Competitive RL: Function Approximation and Partial Observation Advances in Neural Information Processing Systems (NeurIPS), 2023 [PDF] Optimistic Exploration with Learned Features Provably Solves Markov Decision Processes with Neural Dynamics International Conference on Learning Representations (ICLR), 2023 [PDF] Gradient-Variation Bound for Online Convex Optimization with Constraints AAAI Conference on Artificial Intelligence (AAAI), 2023 [PDF] Contrastive UCB: Provably Efficient Contrastive Self-Supervised Learning in Online Reinforcement Learning International Conference on Machine Learning (ICML), 2022 [PDF] [Codes] In-Database Machine Learning with CorgiPile: Stochastic Gradient Descent without Full Data Shuffle International Conference on Management of Data (SIGMOD), 2022 [PDF] [Extended Version] On
Reward-Free RL with Kernel and Neural Function Approximations:
Single-Agent MDP and Markov Game
International Conference on Machine Learning (ICML), 2021 [PDF]
Provably Efficient Fictitious Play Policy Optimization for
Zero-Sum Markov Games with Structured Transitions
International Conference on Machine Learning (ICML), 2021 [PDF] Stylized Neural Painting IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021 [PDF] [Codes] [Project]
Upper Confidence Primal-Dual Reinforcement Learning for CMDP with Adversarial Loss Advances in Neural Information Processing Systems (NeurIPS), 2020 [PDF]
Robust One-Bit Recovery via ReLU Generative Networks:
Near-Optimal Statistical Rate and Global Landscape Analysis
International Conference on Machine Learning (ICML), 2020 [PDF] |
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Academic Service Conference
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