{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,13]],"date-time":"2026-02-13T23:30:02Z","timestamp":1771025402455,"version":"3.50.1"},"reference-count":46,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"12","license":[{"start":{"date-parts":[[2016,12,1]],"date-time":"2016-12-01T00:00:00Z","timestamp":1480550400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"}],"funder":[{"DOI":"10.13039\/501100001039","name":"National Research Foundation","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100001039","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Corp Lab@University"},{"DOI":"10.13039\/100000163","name":"ARC","doi-asserted-by":"publisher","award":["FT130100746"],"award-info":[{"award-number":["FT130100746"]}],"id":[{"id":"10.13039\/100000163","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000163","name":"ARC","doi-asserted-by":"publisher","award":["LP150100671"],"award-info":[{"award-number":["LP150100671"]}],"id":[{"id":"10.13039\/100000163","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Pattern Anal. Mach. Intell."],"published-print":{"date-parts":[[2016,12,1]]},"DOI":"10.1109\/tpami.2016.2533384","type":"journal-article","created":{"date-parts":[[2016,2,23]],"date-time":"2016-02-23T14:08:07Z","timestamp":1456236487000},"page":"2472-2486","source":"Crossref","is-referenced-by-count":12,"title":["Making Trillion Correlations Feasible in Feature Grouping and Selection"],"prefix":"10.1109","volume":"38","author":[{"given":"Yiteng","family":"Zhai","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yew-Soon","family":"Ong","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ivor W.","family":"Tsang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref39","first-page":"33","article-title":"An improved GLMNET for L1-regularized logistic regression and support vector machines","author":"yuan","year":"0","journal-title":"Proc 17th ACM SIGKDD Int Conf Knowl Discovery Data Mining"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/TNN.2010.2044189"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2014.2382599"},{"key":"ref32","first-page":"1687","article-title":"Defragging subgraph features for graph classification","author":"wang","year":"0","journal-title":"Proc ACM Int Conf Inf Knowl Manag"},{"key":"ref31","first-page":"363","article-title":"Core vector machines: Fast SVM training on very large data sets","volume":"6","author":"tsang","year":"2005","journal-title":"J Mach Learn Res"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1126\/science.1215894"},{"key":"ref37","article-title":"Efficient sparse modeling with automatic feature grouping","author":"zhong","year":"2011"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1111\/j.1541-0420.2007.00843.x"},{"key":"ref35","first-page":"1179","article-title":"Consistency of the group lasso and multiple kernel learning","volume":"9","author":"bach","year":"2008","journal-title":"J Mach Learn Res"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1111\/j.1467-9868.2005.00503.x"},{"key":"ref10","article-title":"Multifactorial evolution: Towards evolutionary multitasking","author":"gupta","year":"2015","journal-title":"IEEE Trans Evol Comput"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1038\/ng.311"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1016\/S0378-1119(99)00219-X"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1034\/j.1399-0039.2002.600403.x"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1006\/inco.1995.1038"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1145\/2020408.2020521"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/FOCS.2012.27"},{"key":"ref16","first-page":"1914","author":"pearson","year":"0","journal-title":"The Life and Letters of Francis Galton"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1017\/CBO9780511809071"},{"key":"ref18","first-page":"1022","article-title":"Multi-interval discretization of continuous-valued attributes for classification learning","author":"fayyad","year":"0","journal-title":"Proc Int Joint Conf Artif Intell"},{"key":"ref19","author":"press","year":"1993","journal-title":"Numerical Recipes in C The Art of Scientific Computing"},{"key":"ref28","first-page":"2013","article-title":"Ultrahigh dimensional feature selection: Beyond the linear model","volume":"10","author":"fan","year":"2009","journal-title":"J Mach Learn Res"},{"key":"ref4","first-page":"1455","article-title":"Discovering support and affiliated features from very high dimensions","author":"zhai","year":"0","journal-title":"Proc Int Conf Mach Learning"},{"key":"ref27","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":"ref3","first-page":"856","article-title":"Feature selection for high-dimensional data: A fast correlation-based filter solution","author":"yu","year":"0","journal-title":"Proc Int Conf Mach Learning"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1145\/2339530.2339675"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1098\/rsfs.2011.0051"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pgen.1000587"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/MCI.2014.2326099"},{"key":"ref7","article-title":"Advancing feature selection research","author":"zhao","year":"2011"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2005.159"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/TEVC.2014.2362558"},{"key":"ref1","article-title":"Correlation-based feature selection for machine learning","author":"hall","year":"1999"},{"key":"ref46","doi-asserted-by":"crossref","first-page":"1796","DOI":"10.1109\/TNN.2011.2162000","article-title":"Spectral embedded clustering: A framework for in-sample and out-of-sample spectral clustering","volume":"22","author":"nie","year":"2011","journal-title":"IEEE Trans Neural Netw"},{"key":"ref20","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":"ref45","doi-asserted-by":"publisher","DOI":"10.1162\/089976601750264965"},{"key":"ref22","author":"guyon","year":"2008","journal-title":"Practical Feature Selection From Correlation to Causality"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/TEVC.2013.2281543"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-87481-2_21"},{"key":"ref24","first-page":"344","article-title":"Tighter and convex maximum margin clustering","volume":"5","author":"li","year":"0","journal-title":"Proc Int Conf Artif Intell Statist"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2011.222"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1145\/1150402.1150429"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1145\/2339530.2339674"},{"key":"ref26","first-page":"2491","article-title":"SimpleMKL","volume":"9","author":"rakotomamonjy","year":"2008","journal-title":"J Mach Learn Res"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btm344"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1080\/10556780802712889"}],"container-title":["IEEE Transactions on Pattern Analysis and Machine Intelligence"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/34\/7600475\/07415982.pdf?arnumber=7415982","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,1,12]],"date-time":"2022-01-12T11:42:56Z","timestamp":1641987776000},"score":1,"resource":{"primary":{"URL":"http:\/\/ieeexplore.ieee.org\/document\/7415982\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,12,1]]},"references-count":46,"journal-issue":{"issue":"12"},"URL":"https:\/\/doi.org\/10.1109\/tpami.2016.2533384","relation":{},"ISSN":["0162-8828","2160-9292"],"issn-type":[{"value":"0162-8828","type":"print"},{"value":"2160-9292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2016,12,1]]}}}