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policytree: Policy learning via doubly robust empirical welfare maximization over trees.

, , , , и . J. Open Source Softw., 5 (55): 2232 (2020)

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Zhengyuan Feng

Zhou Zhou

Zhou Zhou

Jun Zhou

Zhou Zhao

 

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Sequential Batch Learning in Finite-Action Linear Contextual Bandits., , , , , и . CoRR, (2020)Simple Agent, Complex Environment: Efficient Reinforcement Learning with Agent States., , и . J. Mach. Learn. Res., (2022)Statistical Learning of Distributionally Robust Stochastic Control in Continuous State Spaces., , , и . CoRR, (2024)Gradient-free Online Learning in Continuous Games with Delayed Rewards., , и . ICML, том 119 из Proceedings of Machine Learning Research, стр. 4172-4181. PMLR, (2020)A Finite Sample Complexity Bound for Distributionally Robust Q-learning., , , и . AISTATS, том 206 из Proceedings of Machine Learning Research, стр. 3370-3398. PMLR, (2023)Finite-Time Last-Iterate Convergence for Multi-Agent Learning in Games., , , и . ICML, том 119 из Proceedings of Machine Learning Research, стр. 6161-6171. PMLR, (2020)Least action routing: Identifying the optimal path in a wireless relay network., , , и . PIMRC, стр. 1-5. IEEE, (2017)Scalable Data Center Power Management via a Global Stress Signal., , , и . GLOBECOM, стр. 1-7. IEEE, (2015)Evasion as a team against a faster pursuer., , , и . ACC, стр. 5368-5373. IEEE, (2013)Repeated games for power control in wireless communications: Equilibrium and regret., , и . CDC, стр. 3603-3610. IEEE, (2016)