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dc.contributor.authorAl-Dujaili, Abdullah
dc.contributor.authorSuresh, S.
dc.date.accessioned2021-09-20T17:17:18Z
dc.date.available2021-09-20T17:17:18Z
dc.date.issued2018-09-29
dc.identifier.urihttps://hdl.handle.net/1721.1/131494
dc.description.abstractAbstract 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.en_US
dc.publisherSpringer USen_US
dc.relation.isversionofhttps://doi.org/10.1007/s10898-018-0709-zen_US
dc.rightsArticle 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.en_US
dc.sourceSpringer USen_US
dc.titleRevisiting norm optimization for multi-objective black-box problems: a finite-time analysisen_US
dc.typeArticleen_US
dc.contributor.departmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
dc.eprint.versionAuthor's final manuscripten_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dc.date.updated2020-09-24T21:26:06Z
dc.language.rfc3066en
dc.rights.holderSpringer Science+Business Media, LLC, part of Springer Nature
dspace.embargo.termsY
dspace.date.submission2020-09-24T21:26:06Z
mit.licensePUBLISHER_POLICY
mit.metadata.statusAuthority Work and Publication Information Needed


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