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Jincheng Mei
Jincheng Mei
Research Scientist, Google DeepMind
Verified email at google.com - Homepage
Title
Cited by
Cited by
Year
On the global convergence rates of softmax policy gradient methods
J Mei, C Xiao, C Szepesvari, D Schuurmans
International Conference on Machine Learning, 6820-6829, 2020
3072020
Locality preserving hashing
K Zhao, H Lu, J Mei
Proceedings of the AAAI Conference on Artificial Intelligence 28 (1), 2014
692014
Leveraging non-uniformity in first-order non-convex optimization
J Mei, Y Gao, B Dai, C Szepesvari, D Schuurmans
International Conference on Machine Learning, 7555-7564, 2021
632021
Escaping the Gravitational Pull of Softmax
J Mei, C Xiao, B Dai, L Li, C Szepesvári, D Schuurmans
Advances in Neural Information Processing Systems 33, 2020
592020
Maximum entropy monte-carlo planning
C Xiao, R Huang, J Mei, D Schuurmans, M Müller
Advances in Neural Information Processing Systems, 9520-9528, 2019
422019
On the optimality of batch policy optimization algorithms
C Xiao, Y Wu, J Mei, B Dai, T Lattimore, L Li, C Szepesvari, ...
International Conference on Machine Learning, 11362-11371, 2021
322021
On principled entropy exploration in policy optimization
J Mei, C Xiao, R Huang, D Schuurmans, M Müller
Proceedings of the 28th International Joint Conference on Artificial …, 2019
292019
Memory-Augmented Monte Carlo Tree Search
C Xiao, J Mei, M Müller
AAAI, 1455-1462, 2018
262018
On the global convergence rates of decentralized softmax gradient play in markov potential games
R Zhang, J Mei, B Dai, D Schuurmans, N Li
Advances in Neural Information Processing Systems 35, 1923-1935, 2022
252022
Understanding the effect of stochasticity in policy optimization
J Mei, B Dai, C Xiao, C Szepesvari, D Schuurmans
Advances in Neural Information Processing Systems 34, 19339-19351, 2021
242021
The Role of Baselines in Policy Gradient Optimization
J Mei, W Chung, V Thomas, B Dai, C Szepesvari, D Schuurmans
Advances in Neural Information Processing Systems 35, 17818-17830, 2022
182022
Understanding and mitigating the limitations of prioritized experience replay
Y Pan, J Mei, A Farahmand, M White, H Yao, M Rohani, J Luo
Uncertainty in Artificial Intelligence, 1561-1571, 2022
182022
Identifying and Tracking Sentiments and Topics from Social Media Texts during Natural Disasters
M Yang, J Mei, H Ji, W Zhao, Z Zhao, X Chen
Proceedings of the 2017 Conference on Empirical Methods in Natural Language …, 2017
182017
Understanding and Leveraging Overparameterization in Recursive Value Estimation
C Xiao, B Dai, J Mei, OA Ramirez, R Gummadi, C Harris, D Schuurmans
International Conference on Learning Representations, 2021
172021
Frequency-based Search-control in Dyna
Y Pan, J Mei, A Farahmand
arXiv preprint arXiv:2002.05822, 2020
172020
Discovering author interest evolution in topic modeling
M Yang, J Mei, F Xu, W Tu, Z Lu
Proceedings of the 39th International ACM SIGIR conference on Research and …, 2016
152016
On unconstrained quasi-submodular function optimization
J Mei, K Zhao, BL Lu
Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015
82015
KL-Entropy-Regularized RL with a Generative Model is Minimax Optimal
T Kozuno, W Yang, N Vieillard, T Kitamura, Y Tang, J Mei, P Ménard, ...
arXiv preprint arXiv:2205.14211, 2022
72022
On the Effect of Log-Barrier Regularization in Decentralized Softmax Gradient Play in Multiagent Systems
R Zhang, J Mei, B Dai, D Schuurmans, N Li
arXiv preprint arXiv:2202.00872, 2022
72022
Value-Incentivized Preference Optimization: A Unified Approach to Online and Offline RLHF
S Cen, J Mei, K Goshvadi, H Dai, T Yang, S Yang, D Schuurmans, Y Chi, ...
arXiv preprint arXiv:2405.19320, 2024
62024
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