Bandit Learning in Many-to-One Matching Markets-Reference-Cited by-同舟云学术

Bandit Learning in Many-to-One Matching Markets

Published:2022-10-17 Issue: Volume: Page:
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Container-title:Proceedings of the 31st ACM International Conference on Information & Knowledge Management
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Author:

Wang Zilong¹,Guo Liya²,Yin Junming³,Li Shuai¹

Affiliation:

1. Shanghai Jiao Tong University, Shanghai, China

2. Xiamen University, Xiamen, China

3. Tepper School of Business, Carnegie Mellon University, Pittsburgh, PA, USA

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3511808.3557248

Reference39 articles.

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3. Soumya Basu , Karthik Abinav Sankararaman , and Abishek Sankararaman . 2021 . Beyond log2(T) Regret for Decentralized Bandits in Matching Markets . In Proceedings of the 38th International Conference on Machine Learning. Soumya Basu, Karthik Abinav Sankararaman, and Abishek Sankararaman. 2021. Beyond log2(T) Regret for Decentralized Bandits in Matching Markets. In Proceedings of the 38th International Conference on Machine Learning.

4. Regret Analysis of Stochastic and Nonstochastic Multi-armed Bandit Problems

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