{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,21]],"date-time":"2026-07-21T18:24:10Z","timestamp":1784658250002,"version":"3.55.0"},"reference-count":57,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"6","license":[{"start":{"date-parts":[[2014,6,1]],"date-time":"2014-06-01T00:00:00Z","timestamp":1401580800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2014,6,1]],"date-time":"2014-06-01T00:00:00Z","timestamp":1401580800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2014,6,1]],"date-time":"2014-06-01T00:00:00Z","timestamp":1401580800000},"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","id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Australian Research Council Linkage","award":["LP0991757"],"award-info":[{"award-number":["LP0991757"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Neural Netw. Learning Syst."],"published-print":{"date-parts":[[2014,6]]},"DOI":"10.1109\/tnnls.2013.2287275","type":"journal-article","created":{"date-parts":[[2013,11,19]],"date-time":"2013-11-19T18:51:01Z","timestamp":1384887061000},"page":"1083-1095","source":"Crossref","is-referenced-by-count":212,"title":["Global and Local Structure Preservation for Feature Selection"],"prefix":"10.1109","volume":"25","author":[{"given":"Xinwang","family":"Liu","sequence":"first","affiliation":[{"name":"School of Computer Science, National University of Defense Technology, Changsha, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lei","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Computer Science and Software Engineering, University of Wollongong, Wollongong, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jian","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Engineering and Information Technology, University of Technology Sydney, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jianping","family":"Yin","sequence":"additional","affiliation":[{"name":"State Key Laboratory of High Performance Computing, National University of Defense Technology, Changsha"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huan","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, AZ, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2012.2225844"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-45080-1_66"},{"key":"ref33","doi-asserted-by":"crossref","first-page":"2323","DOI":"10.1126\/science.290.5500.2323","article-title":"Nonlinear dimensionality reduction by locally linear embedding","volume":"290","author":"roweis","year":"2000","journal-title":"Science"},{"key":"ref32","first-page":"1393","article-title":"Feature selection via dependence maximization","volume":"13","author":"song","year":"2011","journal-title":"J Mach Learn Res"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1023\/A:1025667309714"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2012.2208269"},{"key":"ref37","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":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2005.55"},{"key":"ref35","article-title":"Locality preserving projections","author":"he","year":"2003","journal-title":"Advances in neural information processing systems"},{"key":"ref34","first-page":"119","article-title":"Think globally, fit locally: Unsupervised learning of low dimensional manifolds","volume":"4","author":"saul","year":"2003","journal-title":"J Mach Learn Res"},{"key":"ref28","first-page":"671","article-title":"Trace ratio criterion for feature selection","author":"nie","year":"0","journal-title":"Proc 23rd AAAI Conf Artif Intell"},{"key":"ref27","first-page":"89","article-title":"Eigenvalue sensitive feature selection","author":"jiang","year":"0","journal-title":"Proc 28th ICML"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1145\/1273496.1273641"},{"key":"ref2","first-page":"1813","article-title":"Efficient and robust feature selection via joint ?2,1-norms minimization","author":"nie","year":"2010","journal-title":"Advances in neural information processing systems"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/34.574797"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/TNN.2010.2044189"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/TNN.2011.2128342"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2012.2201748"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1145\/1015330.1015364"},{"key":"ref23","first-page":"325","article-title":"Feature selection via block-regularized regression","author":"kim","year":"0","journal-title":"Proc 24th Conf UAI"},{"key":"ref26","first-page":"1455","article-title":"Discovering support and affiliated features from very high dimensions","author":"zhai","year":"0","journal-title":"Proc 29th ICML"},{"key":"ref25","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":"ref50","first-page":"1683","article-title":"An introduction to nonlinear dimensionality reduction by maximum variance unfolding","author":"weinberger","year":"0","journal-title":"Proc 21st AAAI Conf Artif Intell"},{"key":"ref51","year":"2012","journal-title":"L21RFS"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1017\/CBO9780511809682"},{"key":"ref56","year":"2012","journal-title":"LapScore"},{"key":"ref55","first-page":"78","article-title":"Feature selection ?1 vs. ?2 regularization, and rotational invariance","author":"ng","year":"0","journal-title":"Proc 21st ICML"},{"key":"ref54","article-title":"1-norm support vector machines","author":"zhu","year":"2003","journal-title":"Advances in neural information processing systems"},{"key":"ref53","year":"2012","journal-title":"LLFS"},{"key":"ref52","year":"2012","journal-title":"MRM"},{"key":"ref10","first-page":"845","article-title":"Feature selection for unsupervised learning","volume":"5","author":"dy","year":"2004","journal-title":"J Mach Learn Res"},{"key":"ref11","first-page":"1294","article-title":"Joint feature selection and subspace learning","author":"gu","year":"0","journal-title":"Proc 2nd IJCAI"},{"key":"ref40","first-page":"1027","article-title":"Dimensionality reduction of multimodal labeled data by local fisher discriminant analysis","volume":"8","author":"sugiyama","year":"2007","journal-title":"J Mach Learn Res"},{"key":"ref12","first-page":"1229","article-title":"Feature selection via joint embedding learning and sparse regression","author":"hou","year":"0","journal-title":"Proc 2nd IJCAI"},{"key":"ref13","first-page":"1589","article-title":"?2,1-norm regularized discriminative feature selection for unsupervised learning","author":"yang","year":"0","journal-title":"Proc 2nd IJCAI"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1137\/1.9781611972771.75"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2007.06.014"},{"key":"ref16","doi-asserted-by":"crossref","first-page":"1033","DOI":"10.1109\/TNN.2010.2047114","article-title":"Discriminative semi-supervised feature selection via manifold regularization","volume":"21","author":"xu","year":"2010","journal-title":"IEEE Trans Neural Netw"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2011.222"},{"key":"ref18","doi-asserted-by":"crossref","first-page":"1610","DOI":"10.1109\/TPAMI.2009.190","article-title":"Local-learning-based feature selection for high-dimensional data analysis","volume":"32","author":"sun","year":"2010","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2012.2212721"},{"key":"ref4","author":"duda","year":"2001","journal-title":"Pattern Classification"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2005.159"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1002\/0471200611"},{"key":"ref5","author":"liu","year":"2008","journal-title":"Computational Methods of Feature Selection"},{"key":"ref8","article-title":"Laplacian score for feature selection","author":"he","year":"2005","journal-title":"Advances in neural information processing systems"},{"key":"ref7","first-page":"673","article-title":"Efficient spectral feature selection with minimum redundancy","author":"zhao","year":"0","journal-title":"Proc 24th AAAI Conf Artif Intell"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1162\/089976603321780317"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2007.70799"},{"key":"ref46","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":"ref45","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2006.11.007"},{"key":"ref48","first-page":"1208","article-title":"Neighborhood preserving embedding","author":"he","year":"0","journal-title":"Proc 10th IEEE ICCV"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2011.11.012"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2007.1008"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1137\/1.9781611972764.32"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2007.383040"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/TNN.2007.910733"}],"container-title":["IEEE Transactions on Neural Networks and Learning Systems"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/5962385\/6815990\/06657801.pdf?arnumber=6657801","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,5,9]],"date-time":"2024-05-09T17:34:56Z","timestamp":1715276096000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/6657801\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2014,6]]},"references-count":57,"journal-issue":{"issue":"6"},"URL":"https:\/\/doi.org\/10.1109\/tnnls.2013.2287275","relation":{},"ISSN":["2162-237X","2162-2388"],"issn-type":[{"value":"2162-237X","type":"print"},{"value":"2162-2388","type":"electronic"}],"subject":[],"published":{"date-parts":[[2014,6]]}}}