| Learning mean-field games X Guo, A Hu, R Xu, J Zhang Advances in Neural Information Processing Systems 32, 2019 | 116 | 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 | 103 | 2020 |
| Anderson Accelerated Douglas--Rachford Splitting A Fu, J Zhang, S Boyd SIAM Journal on Scientific Computing 42 (6), A3560-A3583, 2020 | 61 | 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 | 35 | 2021 |
| A general framework for learning mean-field games X Guo, A Hu, R Xu, J Zhang Mathematics of Operations Research, 2022 | 31 | 2022 |
| Robust super-level set estimation using Gaussian processes A Zanette, J Zhang, MJ Kochenderfer Machine Learning and Knowledge Discovery in Databases: European Conference …, 2019 | 21 | 2019 |
| 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 | 11 | 2018 |
| MF-OMO: An optimization formulation of mean-field games X Guo, A Hu, J Zhang arXiv preprint arXiv:2206.09608, 2022 | 6 | 2022 |
| On the global convergence of momentum-based policy gradient Y Ding, J Zhang, J Lavaei arXiv preprint arXiv:2110.10116, 2021 | 6* | 2021 |
| 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 | 4 | 2021 |
| 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 | 4 | 2021 |
| 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 | 1 | 2022 |
| 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 |
| 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 |
| SUPPLEMENTARY MATERIALS: ANDERSON ACCELERATED DOUGLAS–RACHFORD SPLITTING A FU, J ZHANG, S BOYD | | |
| A Brief Introduction to Prox-affine Forms in Convex Optimization J Zhang, A Fu, S Boyd | | |
Stephen BoydProfessor of Electrical Engineering, Computer Science, and Management Science, StanfordBestätigte E-Mail-Adresse bei stanford.edu
