Revisiting norm optimization for multi-objective black-box problems: a finite-time analysis
Name
10898_2018_709_ReferencePDF.pdf
Size
575.15 KB
Format
Adobe PDF
Checksum (MD5)
7bf5f1eab1b6087d86c7efe649dd3fba
Author(s)
Al-Dujaili, Abdullah
Suresh, S.
Date Issued
September 29, 2018
Publisher
Springer US
Version
Author's final manuscript
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.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Terms of Use
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.
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1007/s10898-018-0709-z
