Generic Outlier Detection in Multi-Armed Bandit

Author:

Ban Yikun1,He Jingrui1

Affiliation:

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

Funder

National Science Foundation

U.S. Department of Homeland Security

Publisher

ACM

Reference39 articles.

1. Approximate is better than "exact" for interval estimation of binomial proportions;Agresti Alan;The American Statistician,1998

2. Graph based anomaly detection and description: a survey

3. Active learning in heteroscedastic noise

4. Using confidence bounds for exploitation-exploration trade-offs;Auer Peter;Journal of Machine Learning Research,2002

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