Online discovery of similarity mappings
Rakhlin, Alexander, Abernethy, Jacob, & Bartlett, Peter L. (2007) Online discovery of similarity mappings. In Proceedings of the 24th international conference on Machine learning - ICML '07, Association for Computing Machinery, Oregon State University in Corvallis, Oregon, pp. 767-774.
We consider the problem of choosing, sequentially, a map which assigns elements of a set A to a few elements of a set B. On each round, the algorithm suffers some cost associated with the chosen assignment, and the goal is to minimize the cumulative loss of these choices relative to the best map on the entire sequence. Even though the offline problem of finding the best map is provably hard, we show that there is an equivalent online approximation algorithm, Randomized Map Prediction (RMP), that is efficient and performs nearly as well. While drawing upon results from the "Online Prediction with Expert Advice" setting, we show how RMP can be utilized as an online approach to several standard batch problems. We apply RMP to online clustering as well as online feature selection and, surprisingly, RMP often outperforms the standard batch algorithms on these problems.
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|Item Type:||Conference Paper|
|Keywords:||Randomized Map Prediction (RMP), standard batch algorithms|
|Subjects:||Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100)|
|Divisions:||Past > QUT Faculties & Divisions > Faculty of Science and Technology
Past > Schools > Mathematical Sciences
2007 by the author(s)/owner(s).
|Deposited On:||17 Aug 2011 23:51|
|Last Modified:||29 Feb 2012 14:34|
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