Chi Jin
Princeton University
H-index: 40
North America-United States
Top articles of Chi Jin
Title | Journal | Author(s) | Publication Date |
|---|---|---|---|
Is RLHF More Difficult than Standard RL? A Theoretical Perspective | Advances in Neural Information Processing Systems | Yuanhao Wang Qinghua Liu Chi Jin | 2024/2/13 |
Optimistic natural policy gradient: a simple efficient policy optimization framework for online rl | Thirty-seventh Conference on Neural Information Processing Systems | Qinghua Liu Gellért Weisz András György Chi Jin Csaba Szepesvári | 2023/5/18 |
Context-lumpable stochastic bandits | Advances in Neural Information Processing Systems | Chung-Wei Lee Qinghua Liu Yasin Abbasi Yadkori Chi Jin Tor Lattimore | 2024/2/13 |
Provably Efficient Reinforcement Learning with Linear Function Approximation | Mathematics of Operations Research/Annual Conference on Learning Theory | Chi Jin Zhuoran Yang Zhaoran Wang Michael I Jordan | 2022 |
Is RLHF More Difficult than Standard RL? | arXiv preprint arXiv:2306.14111 | Yuanhao Wang Qinghua Liu Chi Jin | 2023/6/25 |
ZeroSwap: Data-driven Optimal Market Making in DeFi | arXiv preprint arXiv:2310.09413 | Viraj Nadkarni Jiachen Hu Ranvir Rana Chi Jin Sanjeev Kulkarni | 2023/10/13 |
Maximum likelihood estimation is all you need for well-specified covariate shift | arXiv preprint arXiv:2311.15961 | Jiawei Ge Shange Tang Jianqing Fan Cong Ma Chi Jin | 2023/11/27 |
Learning a universal human prior for dexterous manipulation from human preference | arXiv preprint arXiv:2304.04602 | Zihan Ding Yuanpei Chen Allen Z Ren Shixiang Shane Gu Qianxu Wang | 2023/4/10 |
Breaking the curse of multiagency: Provably efficient decentralized multi-agent rl with function approximation | Conference on Learning Theory, 2023 | Yuanhao Wang Qinghua Liu Yu Bai Chi Jin | 2023/2/13 |
Consistency models as a rich and efficient policy class for reinforcement learning | Zihan Ding Chi Jin | 2023/9/29 | |
V-learning—a simple, efficient, decentralized algorithm for multiagent reinforcement learning | Mathematics of Operations Research | Chi Jin Qinghua Liu Yuanhao Wang Tiancheng Yu | 2023/11/17 |
On the provable advantage of unsupervised pretraining | arXiv preprint arXiv:2303.01566 | Jiawei Ge Shange Tang Jianqing Fan Chi Jin | 2023/3/2 |
Optimistic mle: A generic model-based algorithm for partially observable sequential decision making | Qinghua Liu Praneeth Netrapalli Csaba Szepesvari Chi Jin | 2023/6/2 | |
Learning Rationalizable Equilibria in Multiplayer Games | arXiv preprint arXiv:2210.11402 | Yuanhao Wang Dingwen Kong Yu Bai Chi Jin | 2022/10/20 |
Sample-efficient reinforcement learning of partially observable markov games | Advances in Neural Information Processing Systems | Qinghua Liu Csaba Szepesvári Chi Jin | 2022/12/6 |
The power of exploiter: Provable multi-agent rl in large state spaces | Chi Jin Qinghua Liu Tiancheng Yu | 2022/6/28 | |
Near-optimal learning of extensive-form games with imperfect information | Yu Bai Chi Jin Song Mei Tiancheng Yu | 2022/6/28 | |
Learning markov games with adversarial opponents: Efficient algorithms and fundamental limits | Qinghua Liu Yuanhao Wang Chi Jin | 2022/6/28 | |
A Deep Reinforcement Learning Approach for Finding Non-Exploitable Strategies in Two-Player Atari Games | arXiv preprint arXiv:2207.08894 | Zihan Ding Dijia Su Qinghua Liu Chi Jin | 2022/7/18 |
Representation learning for general-sum low-rank markov games | arXiv preprint arXiv:2210.16976 | Chengzhuo Ni Yuda Song Xuezhou Zhang Chi Jin Mengdi Wang | 2022/10/30 |
Co-Authors
