Jin, Tiancheng

7 publications

NeurIPS 2023 Improved Best-of-Both-Worlds Guarantees for Multi-Armed Bandits: FTRL with General Regularizers and Multiple Optimal Arms Tiancheng Jin, Junyan Liu, Haipeng Luo

NeurIPS 2023 No-Regret Online Reinforcement Learning with Adversarial Losses and Transitions Tiancheng Jin, Junyan Liu, Chloé Rouyer, William Chang, Chen-Yu Wei, Haipeng Luo

NeurIPS 2022 Near-Optimal Regret for Adversarial MDP with Delayed Bandit Feedback Tiancheng Jin, Tal Lancewicki, Haipeng Luo, Yishay Mansour, Aviv Rosenberg

NeurIPS 2021 The Best of Both Worlds: Stochastic and Adversarial Episodic MDPs with Unknown Transition Tiancheng Jin, Longbo Huang, Haipeng Luo

ICML 2020 Learning Adversarial Markov Decision Processes with Bandit Feedback and Unknown Transition Chi Jin, Tiancheng Jin, Haipeng Luo, Suvrit Sra, Tiancheng Yu

NeurIPS 2020 Simultaneously Learning Stochastic and Adversarial Episodic MDPs with Known Transition Tiancheng Jin, Haipeng Luo

ACML 2018 Boosting Dynamic Programming with Neural Networks for Solving NP-Hard Problems Feidiao Yang, Tiancheng Jin, Tie-Yan Liu, Xiaoming Sun, Jialin Zhang