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Revisiting norm optimization for multi-objective black-box problems: a finite-time analysis

Author(s)
Al-Dujaili, Abdullah; Suresh, S.
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Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
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Abstract
Abstract The complexity of Pareto fronts imposes a great challenge on the convergence analysis of multi-objective optimization methods. While most theoretical convergence studies have addressed finite-set and/or discrete problems, others have provided probabilistic guarantees, assumed a total order on the solutions, or studied their asymptotic behaviour. In this paper, we revisit the Tchebycheff weighted method in a hierarchical bandits setting and provide a finite-time bound on the Pareto-compliant additive $$\epsilon $$ ϵ -indicator. To the best of our knowledge, this paper is one of few that establish a link between weighted sum methods and quality indicators in finite time.
Date issued
2018-09-29
URI
https://hdl.handle.net/1721.1/131494
Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Publisher
Springer US

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