Learning mean-field games X Guo, A Hu, R Xu, J Zhang Advances in neural information processing systems 32, 2019 | 206 | 2019 |
Globally convergent type-I Anderson acceleration for nonsmooth fixed-point iterations J Zhang, B O'Donoghue, S Boyd SIAM Journal on Optimization 30 (4), 3170-3197, 2020 | 149 | 2020 |
Sample efficient reinforcement learning with REINFORCE J Zhang, J Kim, B O'Donoghue, S Boyd Proceedings of the AAAI conference on artificial intelligence 35 (12), 10887 …, 2021 | 83 | 2021 |
Anderson Accelerated Douglas--Rachford Splitting A Fu, J Zhang, S Boyd SIAM Journal on Scientific Computing 42 (6), A3560-A3583, 2020 | 82 | 2020 |
A general framework for learning mean-field games X Guo, A Hu, R Xu, J Zhang Mathematics of Operations Research 48 (2), 656-686, 2023 | 45 | 2023 |
Robust super-level set estimation using Gaussian processes A Zanette, J Zhang, MJ Kochenderfer Machine Learning and Knowledge Discovery in Databases: European Conference …, 2019 | 34 | 2019 |
On the global optimum convergence of momentum-based policy gradient Y Ding, J Zhang, J Lavaei International Conference on Artificial Intelligence and Statistics, 1910-1934, 2022 | 18 | 2022 |
Beyond exact gradients: Convergence of stochastic soft-max policy gradient methods with entropy regularization Y Ding, J Zhang, J Lavaei arXiv preprint arXiv:2110.10117, 2021 | 17 | 2021 |
MF-OMO: An optimization formulation of mean-field games X Guo, A Hu, J Zhang SIAM Journal on Control and Optimization 62 (1), 243-270, 2024 | 16 | 2024 |
Consistency and computation of regularized mles for multivariate hawkes processes X Guo, A Hu, R Xu, J Zhang arXiv preprint arXiv:1810.02955 (Short version in NeurIPS 2018 Workshop on …, 2018 | 16 | 2018 |
Theoretical guarantees of fictitious discount algorithms for episodic reinforcement learning and global convergence of policy gradient methods X Guo, A Hu, J Zhang Proceedings of the AAAI Conference on Artificial Intelligence 36 (6), 6774-6782, 2022 | 5 | 2022 |
A Markov regime switching model for ultra-short-term wind power prediction based on toeplitz inverse covariance clustering H Fan, X Zhang, S Mei, J Zhang Frontiers in Energy Research 9, 638797, 2021 | 5 | 2021 |
MFGLib: A library for mean-field games X Guo, A Hu, M Santamaria, M Tajrobehkar, J Zhang arXiv preprint arXiv:2304.08630, 2023 | 4 | 2023 |
MESOB: Balancing equilibria & social optimality X Guo, L Li, S Nabi, R Salhab, J Zhang arXiv preprint arXiv:2307.07911, 2023 | 2 | 2023 |
Local analysis of entropy-regularized stochastic soft-max policy gradient methods Y Ding, J Zhang, J Lavaei 2023 European Control Conference (ECC), 1-8, 2023 | 2 | 2023 |
Stabilizing Anderson mixing for accelerated optimization J Zhang Stanford University, 2021 | 1 | 2021 |
Information-Directed Sampling for Reinforcement Learning J Qian, J Zhang MS&E 338 course project supervised by Prof. Benjamin Van Roy & Dr. Abbas …, 2017 | 1 | 2017 |
MF-OML: Online Mean-Field Reinforcement Learning with Occupation Measures for Large Population Games A Hu, J Zhang arXiv preprint arXiv:2405.00282, 2024 | | 2024 |
Joint Graph Learning and Model Fitting in Laplacian Regularized Stratified Models Z Cheng, J Zhang, A Agrawal, S Boyd arXiv preprint arXiv:2305.02573, 2023 | | 2023 |
Particle Filter Network: A Model-free Approach for POMDP P Gao, J Zhang AA 229/CS 239 course project supervised by Prof. Mykel J. Kochenderfer, 2018 | | 2018 |