Finite-time analysis for double Q-learning H Xiong, L Zhao, Y Liang, W Zhang Advances in neural information processing systems 33, 16628-16638, 2020 | 33 | 2020 |
Non-asymptotic convergence of adam-type reinforcement learning algorithms under markovian sampling H Xiong, T Xu, Y Liang, W Zhang Proceedings of the AAAI Conference on Artificial Intelligence 35 (12), 10460 …, 2021 | 30 | 2021 |
Finite-time theory for momentum Q-learning W Bowen, X Huaqing, Z Lin, L Yingbin, Z Wei Uncertainty in Artificial Intelligence, 665-674, 2021 | 20* | 2021 |
Analytical convergence regions of accelerated gradient descent in nonconvex optimization under regularity condition H Xiong, Y Chi, B Hu, W Zhang Automatica 113, 108715, 2020 | 12 | 2020 |
Deterministic policy gradient: Convergence analysis H Xiong, T Xu, L Zhao, Y Liang, W Zhang Uncertainty in Artificial Intelligence, 2159-2169, 2022 | 7 | 2022 |
Analysis of Q-learning with Adaptation and Momentum Restart for Gradient Descent B Weng, H Xiong, Y Liang, W Zhang the Twenty-Ninth International Joint Conference on Artificial Intelligence …, 2020 | 7 | 2020 |
Faster non-asymptotic convergence for double q-learning L Zhao, H Xiong, Y Liang Advances in Neural Information Processing Systems 34, 7242-7253, 2021 | 4 | 2021 |
Reinforcement Learning Algorithms: Acceleration Design and Non-asymptotic Theory H Xiong The Ohio State University, 2021 | 1 | 2021 |
Deterministic Policy Gradient: Convergence Analysis X Huaqing, X Tengyu, L Zhao, L Yingbin, Z Wei | | 2022 |
Finite-time theory of momentum Q-learning L Zhao, B Weng, H Xiong, Y Liang, W Zhang | | 2021 |
Double Q-learning: New Analysis and Sharper Finite-time Bound L Zhao, H Xiong, Y Liang, W Zhang | | 2020 |
CAN ALTQ LEARN FASTER: EXPERIMENTS AND THEORY B Weng, H Xiong, Y Liang, W Zhang | | 2019 |
Finite-Time Theory for Momentum Q-learning (Supplementary material) B Weng, H Xiong, L Zhao, Y Liang, W Zhang | | |
Convergence analysis of accelerated first-order methods for phase retrieval H Xiong, Y Chi, B Hu, W Zhang | | |