{"title":"SketchyCoreSVD: SketchySVD from Random Subsampling of the Data Matrix.","authors":"Chandrajit Bajaj, Yi Wang, Tianming Wang","doi":"10.1109/bigdata47090.2019.9006345","DOIUrl":null,"url":null,"abstract":"<p><p>We present a method called SketchyCoreSVD to compute the near-optimal rank <i>r</i> SVD of a data matrix by building random sketches only from its subsampled columns and rows. We provide theoretical guarantees under incoherence assumptions, and validate the performance of our SketchyCoreSVD method on various large static and time-varying datasets.</p>","PeriodicalId":91601,"journal":{"name":"Proceedings. IEEE International Congress on Big Data","volume":"2019 ","pages":"26-35"},"PeriodicalIF":0.0000,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/bigdata47090.2019.9006345","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings. IEEE International Congress on Big Data","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/bigdata47090.2019.9006345","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2020/2/24 0:00:00","PubModel":"Epub","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
We present a method called SketchyCoreSVD to compute the near-optimal rank r SVD of a data matrix by building random sketches only from its subsampled columns and rows. We provide theoretical guarantees under incoherence assumptions, and validate the performance of our SketchyCoreSVD method on various large static and time-varying datasets.