Multi-facet Contextual Bandits-Reference-Cited by-同舟云学术

Multi-facet Contextual Bandits

Published:2021-08-14 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining
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Author:

Ban Yikun¹,He Jingrui¹,Cook Curtiss B.²

Affiliation:

1. University of Illinois at Urbana-Champaign, Urbana-Champaign, IL, USA

2. Mayo Clinic Arizona, Phoenix, AZ, USA

Funder

U.S. Department of Homeland Security

National Science Foundation

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3447548.3467299

Reference47 articles.

1. Yasin Abbasi-Yadkori Dávid Pál and Csaba Szepesvári. 2011. Improved algorithms for linear stochastic bandits. In Advances in Neural Information Processing Systems. 2312--2320. Yasin Abbasi-Yadkori Dávid Pál and Csaba Szepesvári. 2011. Improved algorithms for linear stochastic bandits. In Advances in Neural Information Processing Systems. 2312--2320.

2. A Neural Networks Committee for the Contextual Bandit Problem

3. Sanjeev Arora Simon S Du Wei Hu Zhiyuan Li Russ R Salakhutdinov and Ruosong Wang. 2019. On exact computation with an infinitely wide neural net. In Advances in Neural Information Processing Systems. 8141--8150. Sanjeev Arora Simon S Du Wei Hu Zhiyuan Li Russ R Salakhutdinov and Ruosong Wang. 2019. On exact computation with an infinitely wide neural net. In Advances in Neural Information Processing Systems. 8141--8150.

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