A Regularization Approach to Metrical Task Systems
Abernethy, Jacob, Bartlett, Peter L., Buchbinder, Niv, & Stanton, Isabelle (2010) A Regularization Approach to Metrical Task Systems. LNCS- Algorithmic Learning Theory, 6331, pp. 270-284.
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We address the problem of constructing randomized online algorithms for the Metrical Task Systems (MTS) problem on a metric δ against an oblivious adversary. Restricting our attention to the class of “work-based” algorithms, we provide a framework for designing algorithms that uses the technique of regularization. For the case when δ is a uniform metric, we exhibit two algorithms that arise from this framework, and we prove a bound on the competitive ratio of each. We show that the second of these algorithms is ln n + O(loglogn) competitive, which is the current state-of-the art for the uniform MTS problem.
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|Item Type:||Journal Article|
|Divisions:||Past > QUT Faculties & Divisions > Faculty of Science and Technology
Past > Schools > Mathematical Sciences
|Copyright Owner:||Copyright 2010 Springer|
|Deposited On:||02 Dec 2011 04:52|
|Last Modified:||11 Mar 2012 05:42|
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