A Survey of Preference-Based Online Learning with Bandit Algorithms-Reference-Cited by-同舟云学术

A Survey of Preference-Based Online Learning with Bandit Algorithms

Published:2014 Issue: Volume: Page:18-39
ISSN:0302-9743
Container-title:Lecture Notes in Computer Science
language:
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Author:

Busa-Fekete Róbert,Hüllermeier Eyke

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-319-11662-4_3

Reference47 articles.

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2. Ailon, N., Karnin, Z., Joachims, T.: Reducing dueling bandits to cardinal bandits. In: Proceedings of the International Conference on Machine Learning (ICML), JMLR W&CP, vol. 32(1), pp. 856–864 (2014)

3. Altman, A., Tennenholtz, M.: Axiomatic foundations for ranking systems. Journal of Artificial Intelligence Research 31(1), 473–495 (2008)

4. Audibert, J.Y., Bubeck, S., Munos, R.: Best arm identification in multi-armed bandits. In: Proceedings of the Twenty-third Conference on Learning Theory (COLT), pp. 41–53 (2010)

5. Auer, P., Cesa-Bianchi, N., Fischer, P.: Finite-time analysis of the multiarmed bandit problem. Machine Learning 47, 235–256 (2002)

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