Revisiting norm optimization for multi-objective black-box problems: a finite-time analysis
Author(s)
Al-Dujaili, Abdullah; Suresh, S.
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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
2018-09-29Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence LaboratoryPublisher
Springer US