Online model selection for restricted covariance matrix adaptation

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

We focus on a variant of covariance matrix adaptation evolution strategy (CMA-ES) with a restricted covariance matrix model, namely VkD-CMA, which is aimed at reducing the internal time complexity and the adaptation time in terms of function evaluations. We tackle the shortage of the VkD-CMA—the model of the restricted covariance matrices needs to be selected beforehand. We propose a novel mechanism to adapt the model online in the VkD-CMA. It eliminates the need for advance model selection and leads to a performance competitive with or even better than the algorithm with a nearly optimal but fixed model.

Original languageEnglish
Title of host publicationParallel Problem Solving from Nature - 14th International Conference, PPSN 2016, Proceedings
EditorsEmma Hart, Ben Paechter, Julia Handl, Manuel López-Ibáñez, Peter R. Lewis, Gabriela Ochoa
PublisherSpringer Verlag
Pages3-13
Number of pages11
ISBN (Print)9783319458229
DOIs
Publication statusPublished - 1 Jan 2016
Externally publishedYes
Event14th International Conference on Parallel Problem Solving from Nature, PPSN 2016 - Edinburgh, United Kingdom
Duration: 17 Sept 201621 Sept 2016

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9921 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference14th International Conference on Parallel Problem Solving from Nature, PPSN 2016
Country/TerritoryUnited Kingdom
CityEdinburgh
Period17/09/1621/09/16

Fingerprint

Dive into the research topics of 'Online model selection for restricted covariance matrix adaptation'. Together they form a unique fingerprint.

Cite this