Projects per year
Fingerprint
Dive into the research topics where Chi Jin is active. These topic labels come from the works of this person. Together they form a unique fingerprint.
- 1 Similar Profiles
Collaborations and top research areas from the last five years
Recent external collaboration on country/territory level. Dive into details by clicking on the dots or
Projects
- 3 Active
-
CAREER: Foundations of Reinforcement Learning under Partial Observability
NSF - National Science Foundation
8/1/23 → 7/31/28
Project: Research project
-
-
RI: Medium: Provable Reinforcement Learning with Function Approximation and Neural Networks
NSF - National Science Foundation
10/1/21 → 9/30/24
Project: Research project
-
Optimistic MLE: A Generic Model-Based Algorithm for Partially Observable Sequential Decision Making
Liu, Q., Netrapalli, P., Szepesvari, C. & Jin, C., Jun 2 2023, STOC 2023 - Proceedings of the 55th Annual ACM Symposium on Theory of Computing. Saha, B. & Servedio, R. A. (eds.). Association for Computing Machinery, p. 363-376 14 p. (Proceedings of the Annual ACM Symposium on Theory of Computing).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
Open Access -
Provably Efficient Reinforcement Learning with Linear Function Approximation
Jin, C., Yang, Z., Wang, Z. & Jordan, M. I., Aug 2023, In: Mathematics of Operations Research. 48, 3, p. 1496-1521 26 p.Research output: Contribution to journal › Article › peer-review
-
A Simple Reward-free Approach to Constrained Reinforcement Learning
Miryoosefi, S. & Jin, C., 2022, In: Proceedings of Machine Learning Research. 162, p. 15666-15698 33 p.Research output: Contribution to journal › Conference article › peer-review
4 Scopus citations -
Efficient Phi-Regret Minimization in Extensive-Form Games via Online Mirror Descent
Bai, Y., Jin, C., Mei, S., Song, Z. & Yu, T., 2022, Advances in Neural Information Processing Systems 35 - 36th Conference on Neural Information Processing Systems, NeurIPS 2022. Koyejo, S., Mohamed, S., Agarwal, A., Belgrave, D., Cho, K. & Oh, A. (eds.). Neural information processing systems foundation, (Advances in Neural Information Processing Systems; vol. 35).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
1 Scopus citations -
Learning Markov Games with Adversarial Opponents: Efficient Algorithms and Fundamental Limits
Liu, Q., Wang, Y. & Jin, C., 2022, In: Proceedings of Machine Learning Research. 162, p. 14036-14053 18 p.Research output: Contribution to journal › Conference article › peer-review
2 Scopus citations