{"title":"An improved PTAS approximation algorithm for k-means clustering problem","authors":"Wang Shou-qiang","doi":"10.1109/URKE.2012.6319592","DOIUrl":null,"url":null,"abstract":"This paper presented an improved (1+ε)-randomized approximation algorithm proposed by Ostrovsky. The running time of the improved algorithm is O(2(O(kα<sup>2</sup>/ε))nd), where d,n denote the dimension and the number of the input points respectively, and α(<;1) represents the separated coefficient. The successful probability is (1/2(1-e<sup>(1/2ε)</sup>))k(1-O(√α)). Compared to the original algorithm, the improved algorithm runs more efficiency.","PeriodicalId":277189,"journal":{"name":"2012 2nd International Conference on Uncertainty Reasoning and Knowledge Engineering","volume":"39 9","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 2nd International Conference on Uncertainty Reasoning and Knowledge Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/URKE.2012.6319592","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
This paper presented an improved (1+ε)-randomized approximation algorithm proposed by Ostrovsky. The running time of the improved algorithm is O(2(O(kα2/ε))nd), where d,n denote the dimension and the number of the input points respectively, and α(<;1) represents the separated coefficient. The successful probability is (1/2(1-e(1/2ε)))k(1-O(√α)). Compared to the original algorithm, the improved algorithm runs more efficiency.
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