{"title":"A tightest convex envelope heuristic to row sparse and rank one matrices","authors":"A. Aghasi, S. Bahmani, J. Romberg","doi":"10.1109/GlobalSIP.2013.6736964","DOIUrl":null,"url":null,"abstract":"The main result of this paper is providing a tight convex envelope to row sparse and rank one matrices which is of major interest in signal recovery applications. The resulting convexification turns out to be the ℓ1 norm of the matrix. This result highlights the fact that a joint convexification approach may not significantly improve the signal recovery process.","PeriodicalId":311464,"journal":{"name":"2013 IEEE Global Conference on Signal and Information Processing","volume":"23 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 IEEE Global Conference on Signal and Information Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/GlobalSIP.2013.6736964","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
The main result of this paper is providing a tight convex envelope to row sparse and rank one matrices which is of major interest in signal recovery applications. The resulting convexification turns out to be the ℓ1 norm of the matrix. This result highlights the fact that a joint convexification approach may not significantly improve the signal recovery process.