Presentation | 2005-03-18 Online Allocation with Risk Information Shigeaki HARADA, Eiji TAKIMOTO, Akira MARUOKA, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | We consider the problem of dynamically apportioning resources among a set of options in a worst-case online framework. The model we investigate is a generalization of the well studied online learning model. In particular, we allow the learner to see as additional information how high the risk of each option is. This assumption is natural in many applications like horse-race betting, where gamblers know odds for all options before placing bets. We apply the Aggregating Algorithm to this problem and give a tight performance bound. The bound we give intuitively implies that the algorithm performs better when faced with options of various risks than when faced with options of the same risk. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | online learning / resource allocation / Hedge algorithm / aggregating algorithm |
Paper # | COMP2004-86 |
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Committee | COMP |
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Conference Date | 2005/3/11(1days) |
Place (in Japanese) | (See Japanese page) |
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Topics (in Japanese) | (See Japanese page) |
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Paper Information | |
Registration To | Theoretical Foundations of Computing (COMP) |
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Language | ENG |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Online Allocation with Risk Information |
Sub Title (in English) | |
Keyword(1) | online learning |
Keyword(2) | resource allocation |
Keyword(3) | Hedge algorithm |
Keyword(4) | aggregating algorithm |
1st Author's Name | Shigeaki HARADA |
1st Author's Affiliation | GSIS, Tohoku University() |
2nd Author's Name | Eiji TAKIMOTO |
2nd Author's Affiliation | GSIS, Tohoku University |
3rd Author's Name | Akira MARUOKA |
3rd Author's Affiliation | GSIS, Tohoku University |
Date | 2005-03-18 |
Paper # | COMP2004-86 |
Volume (vol) | vol.104 |
Number (no) | 743 |
Page | pp.pp.- |
#Pages | 6 |
Date of Issue |