Art
J-GLOBAL ID:201802232940421266
Reference number:18A0731450
Combinatorial bandit prediction with relaxation-based approximation algorithm
緩和ベース近似アルゴリズムによる組合せ詐欺予測
Author (4):
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Material:
Volume:
2018
Issue:
AL-167
Page:
Vol.2018-AL-167,No.4,1-4 (WEB ONLY)
Publication year:
Mar. 01, 2018
JST Material Number:
U0451A
Document type:
Proceedings
Article type:
原著論文
Country of issue:
Japan (JPN)
Language:
ENGLISH (EN)
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Semi thesaurus term:
Thesaurus term/Semi thesaurus term
Keywords indexed to the article.
All keywords is available on JDreamIII(charged).
On J-GLOBAL, this item will be available after more than half a year after the record posted. In addtion, medical articles require to login to MyJ-GLOBAL.
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JST classification (1):
JST classification
Category name(code) classified by JST.
Theory of computation
Reference (6):
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S?bastien Bubeck, Nicol? Cesa-Bianchi, and Sham M. Kakade. Towards minimax policies for online linear optimization with bandit feedback. In COLT 2012 - The 25th Annual Conference on Learning Theory, June 25-27, 2012, Edinburgh, Scotland, pages 41.1-41.14, 2012.
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Nicol? Cesa-Bianchi and G?bor Lugosi. Prediction, learning, and games. Cambridge University Press, 2006.
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Takahiro Fujita, Kohei Hatano, and Eiji Takimoto. Combinatorial online prediction via metarounding. In Algorithmic Learning Theory - 24th International Conference, ALT 2013, Singapore, October 6-9, 2013. Proceedings, pages 68-82, 2013.
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Dan Garber. Efficient online linear optimization with approximation algorithms. In Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 4-9 December 2017, Long Beach, CA, USA, pages 627-635, 2017.
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Sham M. Kakade, Adam Tauman Kalai, and Katrina Ligett. Playing games with approximation algorithms. SIAM J. Comput., 39(3):1088-1106, 2009.
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Terms in the title (5):
Terms in the title
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