Contextual Bandit for Active Learning: Active Thompson Sampling-Reference-Cited by-同舟云学术

Contextual Bandit for Active Learning: Active Thompson Sampling

Published:2014 Issue: Volume: Page:405-412
ISSN:0302-9743
Container-title:Neural Information Processing
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Author:

Bouneffouf Djallel,Laroche Romain,Urvoy Tanguy,Feraud Raphael,Allesiardo Robin

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-319-12637-1_51

Reference11 articles.

1. Agrawal, S., Goyal, N.: Thompson sampling for contextual bandits with linear payoffs. In: ICML (3), pp. 127–135 (2013)

2. Bouneffouf, D.: DRARS, A Dynamic Risk-Aware Recommender System. PhD thesis, Institut National des Télécommunications (2013)

3. Lecture Notes in Computer Science;D. Bouneffouf,2012

4. Chapelle, O., Li, L.: An empirical evaluation of thompson sampling. In: Shawe-Taylor, J., Zemel, R.S., Bartlett, P.L., Pereira, F.C.N., Weinberger, K.Q. (eds.) NIPS, pp. 2249–2257 (2011)

5. Ganti, R., Gray, A.G.: Building bridges: Viewing active learning from the multi-armed bandit lens. CoRR, abs/1309.6830 (2013)

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