There are no files associated with this item.
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.citation.startPage | 119367 | - |
dc.citation.title | INFORMATION SCIENCES | - |
dc.citation.volume | 645 | - |
dc.contributor.author | Choi, Young-Geun | - |
dc.contributor.author | Kim, Gi-Soo | - |
dc.contributor.author | Paik, Seunghoon | - |
dc.contributor.author | Paik, Myunghee Cho | - |
dc.date.accessioned | 2023-12-21T11:43:17Z | - |
dc.date.available | 2023-12-21T11:43:17Z | - |
dc.date.created | 2023-08-22 | - |
dc.date.issued | 2023-10 | - |
dc.description.abstract | Non-stationarity is ubiquitous in human behavior and addressing it in the contextual bandits is challenging. Several works have addressed the problem by investigating semi-parametric contextual bandits and warned that ignoring non-stationarity could harm performances. Another prevalent human behavior is social interaction which has become available in a form of a social network or graph structure. As a result, graph-based contextual bandits have received much attention. In this paper, we propose SemiGraphTS, a novel contextual Thompson-sampling algorithm for a graph-based semi-parametric reward model. Our algorithm is the first to be proposed in this setting. We derive an upper bound of the cumulative regret that can be expressed as a multiple of a factor depending on the graph structure and the order for the semi-parametric model without a graph. We evaluate the proposed and existing algorithms via simulation and real data example. | - |
dc.identifier.bibliographicCitation | INFORMATION SCIENCES, v.645, pp.119367 | - |
dc.identifier.doi | 10.1016/j.ins.2023.119367 | - |
dc.identifier.issn | 0020-0255 | - |
dc.identifier.scopusid | 2-s2.0-85164237798 | - |
dc.identifier.uri | https://scholarworks.unist.ac.kr/handle/201301/65134 | - |
dc.identifier.wosid | 001036367700001 | - |
dc.language | 영어 | - |
dc.publisher | ELSEVIER SCIENCE INC | - |
dc.title | Semi-parametric contextual bandits with graph-Laplacian regularization | - |
dc.type | Article | - |
dc.description.isOpenAccess | FALSE | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Information Systems | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.type.docType | Article | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.subject.keywordAuthor | Contextual multi-armed bandit | - |
dc.subject.keywordAuthor | Graph Laplacian | - |
dc.subject.keywordAuthor | Semi-parametric reward model | - |
dc.subject.keywordAuthor | Thompson sampling | - |
Items in Repository are protected by copyright, with all rights reserved, unless otherwise indicated.
Tel : 052-217-1404 / Email : scholarworks@unist.ac.kr
Copyright (c) 2023 by UNIST LIBRARY. All rights reserved.
ScholarWorks@UNIST was established as an OAK Project for the National Library of Korea.