Natural policy gradient primal-dual method for constrained markov decision processes D Ding, K Zhang, T Basar, M Jovanovic Advances in Neural Information Processing Systems 33, 8378-8390, 2020 | 168 | 2020 |
Provably efficient safe exploration via primal-dual policy optimization D Ding, X Wei, Z Yang, Z Wang, M Jovanovic International Conference on Artificial Intelligence and Statistics, 3304-3312, 2021 | 148 | 2021 |
Non‐linear Mittag–Leffler stabilisation of commensurate fractional‐order non‐linear systems D Ding, D Qi, Q Wang IET Control Theory & Applications 9 (5), 681-690, 2015 | 96 | 2015 |
Independent policy gradient for large-scale markov potential games: Sharper rates, function approximation, and game-agnostic convergence D Ding, CY Wei, K Zhang, M Jovanovic International Conference on Machine Learning, 5166-5220, 2022 | 64 | 2022 |
Asymptotic pseudo-state stabilization of commensurate fractional-order nonlinear systems with additive disturbance D Ding, D Qi, J Peng, Q Wang Nonlinear Dynamics 81, 667-677, 2015 | 48 | 2015 |
Adaptive Mittag‐Leffler stabilization of a class of fractional order uncertain nonlinear systems Q Wang, J Zhang, D Ding, D Qi Asian Journal of Control 18 (6), 2343-2351, 2016 | 36 | 2016 |
Adaptive Mittag-Leffler stabilization of commensurate fractional-order nonlinear systems D Ding, D Qi, Y Meng, L Xu 53rd IEEE Conference on Decision and Control, 6920-6926, 2014 | 36 | 2014 |
Convergence analysis and performance of an extended central force optimization algorithm D Ding, D Qi, X Luo, J Chen, X Wang, P Du Applied Mathematics and Computation 219 (4), 2246-2259, 2012 | 36 | 2012 |
Global exponential stability of primal-dual gradient flow dynamics based on the proximal augmented Lagrangian D Ding, MR Jovanović 2019 American Control Conference (ACC), 3414-3419, 2019 | 21 | 2019 |
Convergence and sample complexity of natural policy gradient primal-dual methods for constrained MDPs D Ding, K Zhang, J Duan, T Başar, MR Jovanović arXiv preprint arXiv:2206.02346, 2022 | 18 | 2022 |
A convergence proof and parameter analysis of central force optimization algorithm D Ding, X Luo, J Chen, X Wang, P Du, Y Guo Journal of Convergence Information Technology 6 (10), 16-23, 2011 | 18 | 2011 |
Fast multi-agent temporal-difference learning via homotopy stochastic primal-dual optimization D Ding, X Wei, Z Yang, Z Wang, MR Jovanović arXiv preprint arXiv:1908.02805, 2019 | 15 | 2019 |
A primal-dual Laplacian gradient flow dynamics for distributed resource allocation problems D Ding, MR Jovanović 2018 Annual American Control Conference (ACC), 5316-5320, 2018 | 15 | 2018 |
An exponentially convergent primal-dual algorithm for nonsmooth composite minimization D Ding, B Hu, NK Dhingra, MR Jovanović 2018 IEEE Conference on Decision and Control (CDC), 4927-4932, 2018 | 10 | 2018 |
Mittag–Leffler synchronization of fractional-order uncertain chaotic systems Q Wang, DS Ding, DL Qi Chinese Physics B 24 (6), 060508, 2015 | 10 | 2015 |
Convergence and optimality of policy gradient primal-dual method for constrained Markov decision processes D Ding, K Zhang, T Başar, MR Jovanović 2022 American Control Conference (ACC), 2851-2856, 2022 | 8 | 2022 |
Global exponential stability of primal-dual gradient flow dynamics based on the proximal augmented Lagrangian: A Lyapunov-based approach D Ding, MR Jovanović 2020 59th IEEE Conference on Decision and Control (CDC), 4836-4841, 2020 | 8 | 2020 |
Last-iterate convergent policy gradient primal-dual methods for constrained mdps D Ding, CY Wei, K Zhang, A Ribeiro Advances in Neural Information Processing Systems 36, 2023 | 6 | 2023 |
Provably efficient generalized lagrangian policy optimization for safe multi-agent reinforcement learning D Ding, X Wei, Z Yang, Z Wang, M Jovanovic Learning for Dynamics and Control Conference, 315-332, 2023 | 5 | 2023 |
Fast multi-agent temporal-difference learning via homotopy stochastic primal-dual method D Ding, X Wei, Z Yang, Z Wang, MR Jovanovic Optimization Foundations for Reinforcement Learning Workshop, 33rd …, 2019 | 5 | 2019 |