{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,30]],"date-time":"2026-09-30T23:24:51Z","timestamp":1790810691496,"version":"4.1.0"},"reference-count":62,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"6","license":[{"start":{"date-parts":[[2017,6,1]],"date-time":"2017-06-01T00:00:00Z","timestamp":1496275200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"}],"funder":[{"name":"China 973 Program","award":["2013CB329404"],"award-info":[{"award-number":["2013CB329404"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61450001"],"award-info":[{"award-number":["61450001"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61263035"],"award-info":[{"award-number":["61263035"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61573270"],"award-info":[{"award-number":["61573270"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004607","name":"Guangxi Natural Science Foundation","doi-asserted-by":"publisher","award":["2012GXNSFGA060004"],"award-info":[{"award-number":["2012GXNSFGA060004"]}],"id":[{"id":"10.13039\/501100004607","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004607","name":"Guangxi Natural Science Foundation","doi-asserted-by":"publisher","award":["2015GXNSFCB139011"],"award-info":[{"award-number":["2015GXNSFCB139011"]}],"id":[{"id":"10.13039\/501100004607","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Guangxi 100 Plan"},{"name":"Guangxi Collaborative Innovation Center of Multi-Source Information Integration and Intelligent Processing"},{"name":"Guangxi Bagui Scholar Teams for Innovation and Research Project"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Neural Netw. Learning Syst."],"published-print":{"date-parts":[[2017,6]]},"DOI":"10.1109\/tnnls.2016.2521602","type":"journal-article","created":{"date-parts":[[2016,2,29]],"date-time":"2016-02-29T14:23:12Z","timestamp":1456755792000},"page":"1263-1275","source":"Crossref","is-referenced-by-count":288,"title":["Robust Joint Graph Sparse Coding for Unsupervised Spectral Feature Selection"],"prefix":"10.1109","volume":"28","author":[{"given":"Xiaofeng","family":"Zhu","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xuelong","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shichao","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chunhua","family":"Ju","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xindong","family":"Wu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref39","first-page":"339","article-title":"Multi-task feature learning via efficient $\\ell _{2,1}$ -norm minimization","author":"liu","year":"2009","journal-title":"Proc 25th Conf UAI"},{"key":"ref38","first-page":"1439","article-title":"Use of the zero norm with linear models and kernel methods","volume":"3","author":"weston","year":"2003","journal-title":"J Mach Learn Res"},{"key":"ref33","first-page":"197","article-title":"Locality preserving projections","author":"he","year":"2003","journal-title":"Proc NIPS"},{"key":"ref32","first-page":"1245","article-title":"Benefitting from the variables that variable selection discards","volume":"3","author":"caruana","year":"2003","journal-title":"J Mach Learn Res"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-01307-2_103"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2014.12.106"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2015.2485163"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2014.2361489"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2009.02.014"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1023\/A:1012487302797"},{"key":"ref60","first-page":"1813","article-title":"Efficient and robust feature selection via joint $\\ell _{2,1}$ -norms minimization","author":"nie","year":"2010","journal-title":"Proc NIPS"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.1145\/1273496.1273592"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1214\/12-STS400"},{"key":"ref28","first-page":"1","article-title":"Feature selection for machine learning classification problems: A recent overview","volume":"42","author":"kotsiantis","year":"2011","journal-title":"Artif Intell Rev"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2014.2332764"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2015.2406194"},{"key":"ref2","doi-asserted-by":"crossref","first-page":"780","DOI":"10.1109\/TNNLS.2013.2281313","article-title":"A unified learning framework for single image super-resolution","volume":"25","author":"yu","year":"2014","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1007\/s10115-013-0702-2"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2008.917359"},{"key":"ref22","article-title":"Subspace regularized sparse multi-task learning for multi-class neurodegenerative disease identification","author":"zhu","year":"0","journal-title":"IEEE Trans Biomed Eng"},{"key":"ref21","first-page":"55","article-title":"Efficient spectral feature selection with minimum redundancy","author":"zhao","year":"2010","journal-title":"Proc AAAI"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2013.2278548"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1137\/1.9781611972832.89"},{"key":"ref26","first-page":"1589","article-title":"$\\ell _{2,1}$ -norm regularized discriminative feature selection for unsupervised learning","author":"yang","year":"2011","journal-title":"Proc 2nd IJCAI"},{"key":"ref25","first-page":"19","article-title":"Online learning for matrix factorization and sparse coding","volume":"11","author":"mairal","year":"2010","journal-title":"J Mach Learn Res"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1214\/09-AOAS271"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2011.2157912"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1109\/JSTSP.2010.2042413"},{"key":"ref58","first-page":"2399","article-title":"Manifold regularization: A geometric framework for learning from labeled and unlabeled examples","volume":"7","author":"belkin","year":"2006","journal-title":"J Mach Learn Res"},{"key":"ref57","first-page":"3089","article-title":"Matrix-similarity based loss function and feature selection for Alzheimer’s disease diagnosis","author":"zhu","year":"2014","journal-title":"Proc IEEE Conf CVPR"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2012.07.018"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2012.2237023"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2015.2403356"},{"key":"ref53","first-page":"857","article-title":"An efficient projection for $l_{1,\\infty }$ regularization","author":"quattoni","year":"2009","journal-title":"Proc 26th Annu ICML"},{"key":"ref52","first-page":"1047","article-title":"Learning sparse SVM for feature selection on very high dimensional datasets","author":"tan","year":"2010","journal-title":"Proceedings of the 27th ICML"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2013.2265601"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1007\/s10115-014-0801-8"},{"key":"ref40","first-page":"2777","article-title":"Structured variable selection with sparsity-inducing norms","volume":"12","author":"jenatton","year":"2011","journal-title":"J Mach Learn Res"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2011.170"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1007\/s10115-015-0844-5"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2010.2090535"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2014.2306419"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2012.02.007"},{"key":"ref17","first-page":"1","article-title":"Canonical feature selection for joint regression and multi-class identification in Alzheimer’s disease diagnosis","author":"zhu","year":"2015","journal-title":"Brain Imag Behavior"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1145\/1835804.1835848"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2010.5539943"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1007\/s10115-013-0713-z"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2014.2369426"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2013.2245914"},{"key":"ref5","doi-asserted-by":"crossref","first-page":"149","DOI":"10.1109\/TCYB.2013.2286496","article-title":"Multiresolution imaging","volume":"44","author":"lu","year":"2014","journal-title":"IEEE Trans Cybern"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2010.99"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2013.2293418"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2012.2233723"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-014-0781-x"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1145\/2457465.2457469"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1198\/106186006X113430"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1038\/381607a0"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1007\/s10994-007-5040-8"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2014.05.078"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1111\/j.1467-9868.2005.00532.x"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1145\/2502081.2502107"},{"key":"ref43","doi-asserted-by":"crossref","first-page":"407","DOI":"10.1214\/009053604000000067","article-title":"Least angle regression","volume":"32","author":"efron","year":"2004","journal-title":"Ann Statist"}],"container-title":["IEEE Transactions on Neural Networks and Learning Systems"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/5962385\/7927806\/07422138.pdf?arnumber=7422138","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,1,12]],"date-time":"2022-01-12T11:39:31Z","timestamp":1641987571000},"score":1,"resource":{"primary":{"URL":"http:\/\/ieeexplore.ieee.org\/document\/7422138\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,6]]},"references-count":62,"journal-issue":{"issue":"6"},"URL":"https:\/\/doi.org\/10.1109\/tnnls.2016.2521602","relation":{},"ISSN":["2162-237X","2162-2388"],"issn-type":[{"value":"2162-237X","type":"print"},{"value":"2162-2388","type":"electronic"}],"subject":[],"published":{"date-parts":[[2017,6]]}}}