{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,27]],"date-time":"2025-10-27T20:44:29Z","timestamp":1761597869912,"version":"3.37.3"},"reference-count":49,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"9","license":[{"start":{"date-parts":[[2018,9,1]],"date-time":"2018-09-01T00:00:00Z","timestamp":1535760000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"}],"funder":[{"name":"GRF Fund from the HKSAR Government"},{"DOI":"10.13039\/501100004377","name":"Hong Kong Polytechnic University","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100004377","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61332011","61272292","61271344","61602540"],"award-info":[{"award-number":["61332011","61272292","61271344","61602540"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Shenzhen Fundamental Research Fund","award":["JCYJ20150403161923528","JCYJ20140508160910917"],"award-info":[{"award-number":["JCYJ20150403161923528","JCYJ20140508160910917"]}]},{"DOI":"10.13039\/501100003009","name":"Science and Technology Development Fund","doi-asserted-by":"publisher","award":["124\/2014\/A3"],"award-info":[{"award-number":["124\/2014\/A3"]}],"id":[{"id":"10.13039\/501100003009","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":[[2018,9]]},"DOI":"10.1109\/tnnls.2017.2761401","type":"journal-article","created":{"date-parts":[[2017,10,31]],"date-time":"2017-10-31T18:38:04Z","timestamp":1509475084000},"page":"4272-4286","source":"Crossref","is-referenced-by-count":24,"title":["Shared Autoencoder Gaussian Process Latent Variable Model for Visual Classification"],"prefix":"10.1109","volume":"29","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5156-0305","authenticated-orcid":false,"given":"Jinxing","family":"Li","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2497-9519","authenticated-orcid":false,"given":"Bob","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5027-5286","authenticated-orcid":false,"given":"David","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref39","first-page":"679","article-title":"Gaussian process latent random field","author":"zhong","year":"2010","journal-title":"Proc 24th AAAI Conf Artif Intell"},{"key":"ref38","volume":"92","author":"chung","year":"1997","journal-title":"Spectral Graph Theory"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2015.2435740"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1145\/1553374.1553391"},{"key":"ref31","first-page":"1","article-title":"Multi-view canonical correlation analysis","author":"rupnik","year":"2010","journal-title":"Proc Conf Data Mining Data Warehouses (SiKDD)"},{"article-title":"A probabilistic interpretation of canonical correlation analysis","year":"2005","author":"bach","key":"ref30"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2014.2362959"},{"key":"ref36","first-page":"328","article-title":"Constructing nonlinear discriminants from multiple data views","author":"diethe","year":"2010","journal-title":"Proc Eur Conf Mach Learn Knowl Discovery Databases"},{"journal-title":"A kernel method for canonical correlation analysis","year":"2006","author":"akaho","key":"ref35"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2012.6247923"},{"key":"ref28","first-page":"73","article-title":"Sparse probabilistic projections","author":"archambeau","year":"2009","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref27","doi-asserted-by":"crossref","first-page":"1131","DOI":"10.1109\/TNNLS.2013.2288062","article-title":"Multiset canonical correlations using globality preserving projections with applications to feature extraction and recognition","volume":"25","author":"yuan","year":"2014","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2014.6853852"},{"key":"ref2","first-page":"2224","article-title":"Relaxed collaborative representation for pattern classification","author":"yang","year":"2012","journal-title":"Proc IEEE Conf Comput Vis Pattern Recognit"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2014.2375634"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2014.2359471"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2012.2205006"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2015.2393857"},{"key":"ref24","first-page":"387","article-title":"Convex subspace representation learning from multi-view data","volume":"1","author":"guo","year":"2013","journal-title":"Proc 27th AAAI Conf Artif Intell"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2015.08.012"},{"key":"ref26","doi-asserted-by":"crossref","first-page":"1909","DOI":"10.1109\/TNNLS.2013.2262949","article-title":"Canonical correlation analysis on data with censoring and error information","volume":"24","author":"sun","year":"2013","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1093\/biomet\/28.3-4.321"},{"key":"ref10","first-page":"329","article-title":"Gaussian process latent variable models for visualisation of high dimensional data","volume":"16","author":"lawrence","year":"2004","journal-title":"Proc Adv Neural Inf Process Syst"},{"article-title":"Shared Gaussian process latent variable models","year":"2009","author":"ek","key":"ref11"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2014.12.016"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1145\/1273496.1273613"},{"journal-title":"Gaussian Processes for Machine Learning","year":"2006","author":"rasmussen","key":"ref13"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1145\/1143844.1143909"},{"key":"ref15","doi-asserted-by":"crossref","first-page":"62","DOI":"10.1007\/978-3-319-06605-9_6","article-title":"Gaussian processes autoencoder for dimensionality reduction","author":"jiang","year":"2014","journal-title":"Proc Pacific-Asia Conf Adv Knowledge Discovery Data Mining"},{"key":"ref16","first-page":"1","article-title":"Sparse autoencoder","volume":"72","author":"ng","year":"2011","journal-title":"CS294A Lecture notes Stanford University"},{"key":"ref17","first-page":"689","article-title":"Multimodal deep learning","author":"ngiam","year":"2011","journal-title":"Proc 28th Int Conf Mach Learn (ICML)"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2016.2523563"},{"key":"ref19","doi-asserted-by":"crossref","first-page":"1309","DOI":"10.1109\/TCSVT.2014.2381471","article-title":"Background prior-based salient object detection via deep reconstruction residual","volume":"25","author":"han","year":"2015","journal-title":"IEEE Trans Circuits Syst Video Technol"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.461"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2016.09.031"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2015.2399233"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2013.2238682"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1002\/0470013192.bsa068"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2015.2510509"},{"key":"ref49","first-page":"1083","article-title":"On deep multi-view representation learning","author":"wang","year":"2015","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1162\/0899766042321814"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206594"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1145\/1873951.1873987"},{"key":"ref48","first-page":"1247","article-title":"Deep canonical correlation analysis","author":"andrew","year":"2013","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref47","first-page":"381","article-title":"Learning systems of concepts with an infinite relational model","volume":"1","author":"kemp","year":"2006","journal-title":"Proc 21st Nat Conf Artif Intell"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2013.142"},{"key":"ref41","first-page":"2065","article-title":"Implicitly constrained Gaussian process regression for monocular non-rigid pose estimation","author":"salzmann","year":"2010","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1145\/1646396.1646452"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2013.140"}],"container-title":["IEEE Transactions on Neural Networks and Learning Systems"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/5962385\/8440865\/08091103.pdf?arnumber=8091103","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,1,26]],"date-time":"2022-01-26T16:00:49Z","timestamp":1643212849000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8091103\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,9]]},"references-count":49,"journal-issue":{"issue":"9"},"URL":"https:\/\/doi.org\/10.1109\/tnnls.2017.2761401","relation":{},"ISSN":["2162-237X","2162-2388"],"issn-type":[{"type":"print","value":"2162-237X"},{"type":"electronic","value":"2162-2388"}],"subject":[],"published":{"date-parts":[[2018,9]]}}}