{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T19:23:20Z","timestamp":1740165800563,"version":"3.37.3"},"reference-count":39,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"11","license":[{"start":{"date-parts":[[2019,11,1]],"date-time":"2019-11-01T00:00:00Z","timestamp":1572566400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2019,11,1]],"date-time":"2019-11-01T00:00:00Z","timestamp":1572566400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2019,11,1]],"date-time":"2019-11-01T00:00:00Z","timestamp":1572566400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61663049","61165012","2019010108203008"],"award-info":[{"award-number":["61663049","61165012","2019010108203008"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Neural Netw. Learning Syst."],"published-print":{"date-parts":[[2019,11]]},"DOI":"10.1109\/tnnls.2019.2927819","type":"journal-article","created":{"date-parts":[[2019,8,9]],"date-time":"2019-08-09T19:45:21Z","timestamp":1565379921000},"page":"3517-3527","source":"Crossref","is-referenced-by-count":4,"title":["Low-Rank Matrix Learning Using Biconvex Surrogate Minimization"],"prefix":"10.1109","volume":"30","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7398-2285","authenticated-orcid":false,"given":"En-Liang","family":"Hu","sequence":"first","affiliation":[]},{"given":"James T.","family":"Kwok","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1007\/s10107-004-0552-5"},{"key":"ref38","first-page":"329","article-title":"Large-scale convex minimization with a low-rank constraint","author":"shalev-shwartz","year":"2011","journal-title":"Proc 28th Int Conf Mach Learn"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1080\/10556780500286582"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1137\/080716542"},{"journal-title":"Numerical Optimization","year":"2006","author":"nocedal","key":"ref31"},{"article-title":"Block coordinate descent for regularized multi-convex optimization","year":"2012","author":"xu","key":"ref30"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.2307\/2284239"},{"key":"ref36","first-page":"1313","article-title":"A family of simple non-parametric kernel learning algorithms","volume":"12","author":"zhuang","year":"2011","journal-title":"J Mach Learn Res"},{"key":"ref35","first-page":"379","article-title":"Accelerated proximal gradient methods for nonconvex programming","author":"li","year":"2015","journal-title":"Proc Adv Neural Inf Process Syst (NIPS)"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1007\/s10107-015-0871-8"},{"key":"ref10","first-page":"179","article-title":"Efficient learning with a family of nonconvex regularizers by redistributing nonconvexity","author":"yao","year":"2017","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref11","article-title":"Convex optimization without projection steps","author":"jaggi","year":"2011","journal-title":"arXiv 1108 1170"},{"key":"ref12","first-page":"1","article-title":"A hybrid algorithm for convex semidefinite optimization","author":"laue","year":"2012","journal-title":"Proc 29th Int Conf Mach Learn"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1007\/s10107-002-0352-8"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1137\/080731359"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1007\/s10898-008-9328-4"},{"key":"ref16","first-page":"306","article-title":"Efficient kernel learning from side information using ADMM","author":"hu","year":"2013","journal-title":"Proc Int Joint Conf Artif Intell"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206852"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1561\/2200000016"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1137\/120887795"},{"key":"ref28","doi-asserted-by":"crossref","DOI":"10.1007\/978-1-4419-8853-9","author":"nesterov","year":"2004","journal-title":"Introductory Lectures on Convex Optimization A Basic Course"},{"key":"ref4","first-page":"27","article-title":"Learning the kernel matrix with semidefinite programming","volume":"5","author":"lanckriet","year":"2004","journal-title":"J Mach Learn Res"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1137\/120887679"},{"key":"ref3","first-page":"1473","article-title":"Distance metric learning for large margin nearest neighbor classification","author":"weinberger","year":"2006","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1007\/s11222-008-9111-x"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1007\/BF01584660"},{"key":"ref5","first-page":"209","article-title":"BCDNPKL: Scalable non-parametric kernel learning using block coordinate descent","author":"hu","year":"2011","journal-title":"Proc 28th Int Conf Mach Learn"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1137\/1.9781611970791"},{"key":"ref7","first-page":"1329","article-title":"Maximum-margin matrix factorization","author":"srebro","year":"2005","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref2","first-page":"505","article-title":"Distance metric learning with application to clustering with side-information","author":"xing","year":"2002","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1007\/s10107-006-0001-8"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1137\/050645506"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1007\/s10107-015-0892-3"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1198\/jasa.2011.tm09738"},{"key":"ref21","first-page":"28","article-title":"Feature clustering for accelerating parallel coordinate descent","author":"scherrer","year":"2012","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1145\/1390156.1390208"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1007\/s10107-012-0614-z"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1137\/16M1085905"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1145\/2020408.2020577"}],"container-title":["IEEE Transactions on Neural Networks and Learning Systems"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/5962385\/8886738\/08793230.pdf?arnumber=8793230","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,7,13]],"date-time":"2022-07-13T21:14:41Z","timestamp":1657746881000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8793230\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,11]]},"references-count":39,"journal-issue":{"issue":"11"},"URL":"https:\/\/doi.org\/10.1109\/tnnls.2019.2927819","relation":{},"ISSN":["2162-237X","2162-2388"],"issn-type":[{"type":"print","value":"2162-237X"},{"type":"electronic","value":"2162-2388"}],"subject":[],"published":{"date-parts":[[2019,11]]}}}