Prati
Che Wang
Che Wang
PhD student, NYU Tandon CSE Shanghai Track
Potvrđena adresa e-pošte na nyu.edu - Početna stranica
Naslov
Citirano
Citirano
Godina
Randomized ensembled double q-learning: Learning fast without a model
X Chen, C Wang, Z Zhou, K Ross
International Conference on Learning Representations (ICLR 2021), 2021
2982021
Bail: Best-action imitation learning for batch deep reinforcement learning
X Chen, Z Zhou, Z Wang, C Wang, Y Wu, K Ross
Advances in Neural Information Processing Systems (NeurIPS 2020) 33, 18353-18363, 2020
1482020
Striving for simplicity and performance in off-policy DRL: Output normalization and non-uniform sampling
C Wang, Y Wu, Q Vuong, K Ross
International Conference on Machine Learning (ICML 2020), 10070-10080, 2020
115*2020
Vrl3: A data-driven framework for visual deep reinforcement learning
C Wang, X Luo, K Ross, D Li
Advances in Neural Information Processing Systems 35, 32974-32988, 2022
462022
Portfolio online evolution in StarCraft
C Wang, P Chen, Y Li, C Holmgård, J Togelius
Proceedings of the AAAI Conference on Artificial Intelligence and …, 2016
352016
On the convergence of the monte carlo exploring starts algorithm for reinforcement learning
C Wang, S Yuan, K Shao, K Ross
International Conference on Learning Representations (ICLR 2022), 2020
262020
Reinforcement learning with automated auxiliary loss search
T He, Y Zhang, K Ren, M Liu, C Wang, W Zhang, Y Yang, D Li
Advances in neural information processing systems 35, 1820-1834, 2022
182022
Aggressive Q-learning with ensembles: achieving both high sample efficiency and high asymptotic performance
Y Wu, X Chen, C Wang, Y Zhang, KW Ross
arXiv preprint arXiv:2111.09159, 2021
102021
Pre-training with Synthetic Data Helps Offline Reinforcement Learning
Z Wang, C Wang, Z Dong, K Ross
International Conference on Learning Representations (ICLR 2024), 2023
42023
On the convergence of monte carlo ucb for random-length episodic mdps
Z Dong, C Wang, K Ross
arXiv preprint arXiv:2209.02864, 2022
42022
Sample-Efficient Deep Reinforcement Learning for Continuous Control
C Wang
New York University Tandon School of Engineering, 2023
2023
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