Learning in queues

Author:

Gaujal Bruno

Publisher

Springer Science and Business Media LLC

Subject

Computational Theory and Mathematics,Management Science and Operations Research,Computer Science Applications

Reference14 articles.

1. Anselmi, J., Gaujal, B., Rebuffi, L.-S.: Optimal speed profile of a DVFS processor under soft deadlines. In: Performance Evaluation. Elsevier (2021). (to appear)

2. Asanjarani, A., Nazarathy, Y., Taylor, P.: A survey of parameter and state estimation in queues. Queueing Syst. 97, 39–80 (2021)

3. Azar, M.G., Osband, I., Munos, R.: Minimax regret bounds for reinforcement learning. In: International Conference on Machine Learning, pp. 263–272. PMLR (2017)

4. Gast, N., Gaujal, B., Khun, K.: Reinforcement learning for Markovian bandits: is posterior sampling more scalable than optimism? Technical Report hal-03262006, HAL-Inria (June 2021)

5. Jaksch, T., Ortner, R., Auer, P.: Near-optimal regret bounds for reinforcement learning. J. Mach. Learn. Res. 11(4), 1563–1600 (2010)

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Lyapunov Meets Thompson: Learning-Based Energy-Efficient UAV Communication with Queuing Stability Constraints;IEEE INFOCOM 2023 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS);2023-05-20

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