{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,28]],"date-time":"2025-10-28T15:03:45Z","timestamp":1761663825780,"version":"3.37.3"},"reference-count":68,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"12","license":[{"start":{"date-parts":[[2019,12,1]],"date-time":"2019-12-01T00:00:00Z","timestamp":1575158400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2019,12,1]],"date-time":"2019-12-01T00:00:00Z","timestamp":1575158400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2019,12,1]],"date-time":"2019-12-01T00:00:00Z","timestamp":1575158400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"NSF IIS","award":["1651902"],"award-info":[{"award-number":["1651902"]}]},{"DOI":"10.13039\/100000183","name":"Army Research Office","doi-asserted-by":"publisher","award":["W911NF-17-1-0367"],"award-info":[{"award-number":["W911NF-17-1-0367"]}],"id":[{"id":"10.13039\/100000183","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Knowl. Data Eng."],"published-print":{"date-parts":[[2019,12,1]]},"DOI":"10.1109\/tkde.2018.2875712","type":"journal-article","created":{"date-parts":[[2018,10,12]],"date-time":"2018-10-12T19:00:14Z","timestamp":1539370814000},"page":"2319-2331","source":"Crossref","is-referenced-by-count":29,"title":["Feature Selection with Unsupervised Consensus Guidance"],"prefix":"10.1109","volume":"31","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0821-8640","authenticated-orcid":false,"given":"Hongfu","family":"Liu","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7686-8784","authenticated-orcid":false,"given":"Ming","family":"Shao","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5098-2853","authenticated-orcid":false,"given":"Yun","family":"Fu","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2017.2650229"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1145\/2783258.2783287"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2013.03.006"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1137\/1.9781611974010.86"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btq226"},{"key":"ref30","first-page":"74","article-title":"Filters, wrappers and a boosting-based hybrid for feature selection","author":"das","year":"2001","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref37","first-page":"583","article-title":"Cluster ensembles&#x2014;A knowledge reuse framework for combining partitions","volume":"3","author":"strehl","year":"2002","journal-title":"J Mach Learn Res"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2005.113"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btx167"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2014.2316512"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2016.0039"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2017.2763945"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2015.18"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2017\/300"},{"key":"ref28","first-page":"801","article-title":"Efficient sparse coding algorithms","author":"lee","year":"2006","journal-title":"Proc Int Conf Neural Inf Process"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.1145\/2783258.2783345"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2006.111"},{"key":"ref65","doi-asserted-by":"publisher","DOI":"10.1145\/1557019.1557115"},{"key":"ref66","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-37331-2_26"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2008.79"},{"key":"ref67","first-page":"686","article-title":"Cluster structure preserving unsupervised feature selection for multi-view tasks","volume":"17","author":"hong","year":"2016","journal-title":"Neurocomput"},{"key":"ref68","doi-asserted-by":"publisher","DOI":"10.1137\/1.9781611972832.30"},{"key":"ref2","first-page":"37","article-title":"From data mining to knowledge discovery in databases","volume":"17","author":"fayyad","year":"1996","journal-title":"AI Mag"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1145\/276304.276314"},{"key":"ref20","first-page":"1874","article-title":"Consensus guided unsupervised feature selection","author":"liu","year":"2016","journal-title":"Proc AAAI Conf Artif Intell"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/34.990133"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2005.66"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.3233\/IDA-2002-6605"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2009.23"},{"key":"ref26","first-page":"641","article-title":"Feature selection in mixture-based clustering","author":"law","year":"2003","journal-title":"Advances Neural Inf Process Syst"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2010.215"},{"key":"ref50","first-page":"2153","article-title":"On the nystr&#x00F6;m method for approximating a gram matrix for improved kernel-based learning","volume":"6","author":"drineas","year":"2005","journal-title":"J Mach Learn Res"},{"key":"ref51","first-page":"269","article-title":"A novel greedy algorithm for nystrm approximation","author":"farahat","year":"2011","journal-title":"Proc 14th Int Conf Artif Intell Statist"},{"key":"ref59","first-page":"387","article-title":"Convex subspace representation learning from multi-view data","author":"guo","year":"2013","journal-title":"Proc AAAI Conf Artif Intell"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-013-1362-6"},{"key":"ref57","first-page":"iii-352","article-title":"Multi-view clustering and feature learning via structured sparsity","author":"wang","year":"2013","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref56","first-page":"133","article-title":"Non-redundant multi-view clustering via orthogonalization","author":"ying","year":"2007","journal-title":"Proc Int Conf Data Mining"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2004.10095"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1145\/1014052.1014118"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2003.1238361"},{"key":"ref52","first-page":"1060","article-title":"Ensemble nystrom method","author":"kumar","year":"2009","journal-title":"Proc Int Conf Neural Inf Process"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1145\/1273496.1273641"},{"key":"ref11","article-title":"Feature selection for clustering: A review","volume":"29","author":"alelyani","year":"2013","journal-title":"Data Clustering Algorithms and Applications"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939813"},{"key":"ref12","first-page":"507","article-title":"Laplacian score for feature selection","author":"he","year":"2005","journal-title":"Proc 18th Int Conf Neural Inf Process Syst"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2005.159"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1145\/1835804.1835848"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2013.65"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1137\/1.9781611972771.75"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2010.195"},{"key":"ref18","first-page":"1589","article-title":"l2, 1-norm regularized discriminative feature selection for unsupervised learning","author":"yang","year":"2011","journal-title":"Proc Int Joint Conf Artif Intell"},{"key":"ref19","first-page":"1026","article-title":"Unsupervised feature selection using nonnegative spectral analysis","author":"li","year":"2012","journal-title":"Proc AAAI Conf Artif Intell"},{"key":"ref4","doi-asserted-by":"crossref","first-page":"69","DOI":"10.1109\/TNNLS.2013.2248094","article-title":"PCA feature extraction for change detection in multidimensional unlabeled data","volume":"25","author":"faithfull","year":"2014","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"key":"ref3","first-page":"1157","article-title":"An introduction to variable and feature selection","volume":"3","author":"guyon","year":"2003","journal-title":"J Mach Learn Res"},{"key":"ref6","first-page":"1855","article-title":"Feature selection for unsupervised and supervised inference: The emergence of sparsity in a weight-based approach","volume":"6","author":"wolf","year":"2005","journal-title":"J Mach Learn Res"},{"key":"ref5","first-page":"625","article-title":"Why does unsupervised pre-training help deep learning?","volume":"11","author":"erhan","year":"2010","journal-title":"J Mach Learn Res"},{"key":"ref8","first-page":"1813","article-title":"Efficient and robust feature selection via joint l2, 1-norms minimization","author":"nie","year":"2010","journal-title":"Proc Int Conf Neural Inf Process"},{"journal-title":"Pattern Recognition","year":"2008","author":"theodoridis","key":"ref7"},{"key":"ref49","first-page":"1813","article-title":"Efficient and robust feature selection via joint $\\ell _{2,1}$?2,1-norms minimization","author":"nie","year":"2010","journal-title":"Proc Int Conf Neural Inf Process"},{"key":"ref9","first-page":"845","article-title":"Feature selection for unsupervised learning","volume":"5","author":"dy","year":"2004","journal-title":"J Mach Learn Res"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1145\/1460797.1460800"},{"key":"ref45","first-page":"1546","article-title":"Simultaneous clustering and ensemble","author":"tao","year":"2017","journal-title":"Proc 31st AAAI Conf Artif Intell"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1023\/A:1010924920739"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2017\/396"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1145\/2983323.2983745"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1007\/s10618-017-0539-5"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2007.1138"},{"key":"ref43","article-title":"Robust spectral ensemble clustering via rank minimization","author":"tao","year":"2018","journal-title":"ACM Trans Knowl Discovery Data"}],"container-title":["IEEE Transactions on Knowledge and Data Engineering"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/69\/8893432\/08490589.pdf?arnumber=8490589","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,7,13]],"date-time":"2022-07-13T20:47:12Z","timestamp":1657745232000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8490589\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,12,1]]},"references-count":68,"journal-issue":{"issue":"12"},"URL":"https:\/\/doi.org\/10.1109\/tkde.2018.2875712","relation":{},"ISSN":["1041-4347","1558-2191","2326-3865"],"issn-type":[{"type":"print","value":"1041-4347"},{"type":"electronic","value":"1558-2191"},{"type":"electronic","value":"2326-3865"}],"subject":[],"published":{"date-parts":[[2019,12,1]]}}}