论文信息 - Learning To Maximize Welfare with a Reusable Resource

Learning To Maximize Welfare with a Reusable Resource

ACM Reference Format: Matthew Faw, Orestis Papadigenopoulos, Constantine Caramanis, and Sanjay Shakkottai. 2022. Learning To Maximize Welfare with a Reusable Resource. In Abstract Proceedings of the 2022 ACM SIGMETRICS/IFIP PERFORMANCE Joint International Conference on Measurement and Modeling of Computer Systems (SIGMETRICS/PERFORMANCE ’22 Abstracts), June 6–10, 2022, Mumbai, India. ACM, New York, NY, USA, 2 pages. https://doi.org/10. 1145/3489048.3530960

S. Shakkottai | C. Caramanis | O. Papadigenopoulos | Matthew Faw

[1] Siddhartha Banerjee,et al. The Bayesian Prophet: A Low-Regret Framework for Online Decision Making , 2018, SIGMETRICS.

[2] The Bayesian Prophet , 2019, SIGMETRICS.

[3] Andreas Tönnis,et al. Think Eternally: Improved Algorithms for the Temp Secretary Problem and Extensions , 2016, ESA.

[4] Haim Kaplan,et al. The Temp Secretary Problem , 2015, ESA.

[5] Albert N. Shiryaev,et al. Optimal Stopping Rules , 1980, International Encyclopedia of Statistical Science.

[6] E. Samuel-Cahn. Comparison of Threshold Stop Rules and Maximum for Independent Nonnegative Random Variables , 1984 .

[7] G. Simons. Great Expectations: Theory of Optimal Stopping , 1973 .