{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,7]],"date-time":"2026-08-07T14:31:24Z","timestamp":1786113084881,"version":"3.56.0"},"reference-count":65,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"3","license":[{"start":{"date-parts":[[2022,3,1]],"date-time":"2022-03-01T00:00:00Z","timestamp":1646092800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2022,3,1]],"date-time":"2022-03-01T00:00:00Z","timestamp":1646092800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,3,1]],"date-time":"2022-03-01T00:00:00Z","timestamp":1646092800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"National Key Research and Development Project of China","award":["2017YFB1002201"],"award-info":[{"award-number":["2017YFB1002201"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61625204"],"award-info":[{"award-number":["61625204"]}],"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":["61971296"],"award-info":[{"award-number":["61971296"]}],"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":["U19A2078"],"award-info":[{"award-number":["U19A2078"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Ministry of Education and China Mobile Research Foundation Project","award":["MCM20180405"],"award-info":[{"award-number":["MCM20180405"]}]},{"name":"Sichuan Science and Technology Planning Project","award":["2019YFG0495"],"award-info":[{"award-number":["2019YFG0495"]}]},{"name":"Sichuan Science and Technology Planning Project","award":["2019YFH0075"],"award-info":[{"award-number":["2019YFH0075"]}]},{"name":"Sichuan Science and Technology Planning Project","award":["2018GZDZX0030"],"award-info":[{"award-number":["2018GZDZX0030"]}]},{"name":"SCU&Luzhou Cooperation Project","award":["2019CDLZ-07"],"award-info":[{"award-number":["2019CDLZ-07"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Cybern."],"published-print":{"date-parts":[[2022,3]]},"DOI":"10.1109\/tcyb.2020.2984489","type":"journal-article","created":{"date-parts":[[2020,5,4]],"date-time":"2020-05-04T19:36:26Z","timestamp":1588620986000},"page":"1588-1601","source":"Crossref","is-referenced-by-count":14,"title":["Deep Semisupervised Class- and Correlation-Collapsed Cross-View Learning"],"prefix":"10.1109","volume":"52","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4821-3334","authenticated-orcid":false,"given":"Xu","family":"Wang","sequence":"first","affiliation":[{"name":"College of Computer Science, Sichuan University, Chengdu, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3868-3997","authenticated-orcid":false,"given":"Peng","family":"Hu","sequence":"additional","affiliation":[{"name":"Institute for Infocomm Research, A&#x002A;STAR, Singapore"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pei","family":"Liu","sequence":"additional","affiliation":[{"name":"College of Computer Science, Sichuan University, Chengdu, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0987-8472","authenticated-orcid":false,"given":"Dezhong","family":"Peng","sequence":"additional","affiliation":[{"name":"College of Computer Science, Sichuan University, Chengdu, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1145\/1873951.1873987"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2016.2519449"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2017.2705068"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2011.5995350"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2015.2435740"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1145\/2578726.2578728"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2016.2646180"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2010.5540112"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2010.5540120"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2018.07.031"},{"key":"ref11","first-page":"5092","article-title":"COMIC: Multi-view clustering without parameter selection","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Peng"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2019\/356"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1093\/biomet\/28.3-4.321"},{"key":"ref14","first-page":"1359","article-title":"Randomized nonlinear component analysis","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Lopez-Paz"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2013.2276704"},{"key":"ref16","first-page":"1247","article-title":"Deep canonical correlation analysis","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Andrew"},{"key":"ref17","first-page":"1083","article-title":"On deep multi-view representation learning","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Wang"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1145\/3123266.3123326"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01246-5_42"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2017.2742704"},{"key":"ref21","first-page":"3846","article-title":"Cross-media shared representation by hierarchical learning with multiple deep networks","volume-title":"Proc. Int. Joint Conf. Artif. Intell. (IJCAI)","author":"Peng"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1145\/3284750"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2018\/365"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1142\/s012906570000034x"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1162\/153244303768966085"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2012.2215617"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2018.2848470"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2018.2827036"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1038\/nature14539"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1561\/2200000006"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/TEVC.2019.2916183"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.285"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.01064"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1145\/3343031.3351078"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2007.1037"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/34.598228"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00526"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v32i1.11419"},{"key":"ref39","first-page":"425","article-title":"Learning multi-view neighborhood preserving projections","volume-title":"Proc. 28th Int. Conf. Mach. Learn.","author":"Quadrianto"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-33868-7_24"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/BTAS.2013.6712686"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2015.2400779"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2017.2723841"},{"key":"ref44","first-page":"451","article-title":"Metric learning by collapsing classes","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Globerson"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1145\/279943.279962"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2005.186"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01267-0_9"},{"key":"ref48","first-page":"2014","article-title":"Tri-net for semi-supervised deep learning","volume-title":"Proc. IJCAI","author":"Dong-DongChen"},{"key":"ref49","first-page":"1","article-title":"Multi-view canonical correlation analysis","volume-title":"Proc. Conf. Data Min. Data Warehouses (SiKDD)","author":"Rupnik"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2019.01.017"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.3156\/jsoft.29.5_177_2"},{"key":"ref52","first-page":"507","article-title":"Large-margin softmax loss for convolutional neural networks","volume-title":"Proc. Int. Conf. Mach. Learn. (ICML)","author":"Liu"},{"key":"ref53","first-page":"513","article-title":"Neighbourhood components analysis","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Goldberger"},{"key":"ref54","first-page":"857","article-title":"Stochastic neighbor embedding","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Hinton"},{"key":"ref55","volume-title":"Adam: A method for stochastic optimization","author":"Kingma","year":"2014"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.123"},{"key":"ref57","volume-title":"Very deep convolutional networks for large-scale image recognition","author":"Simonyan","year":"2014"},{"key":"ref58","first-page":"3111","article-title":"Distributed representations of words and phrases and their compositionality","volume-title":"Proc. Int. Conf. Neural Inf. Process. Syst.","author":"Mikolov"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.3115\/v1\/D14-1181"},{"key":"ref60","first-page":"139","article-title":"Collecting image annotations using Amazon\u2019s Mechanical Turk","volume-title":"Proc. NAACL HLT Workshop Creating Speech Lang. Data Amazon\u2019s Mech. Turk,","author":"Rashtchian"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v29i1.9598"},{"key":"ref62","first-page":"28","article-title":"Learning from multiple partially observed views-an application to multilingual text categorization","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Amini"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.1109\/5.726791"},{"key":"ref64","volume-title":"A Tutorial on Principal Components Analysis","author":"Smith","year":"2002"},{"key":"ref65","doi-asserted-by":"publisher","DOI":"10.1007\/s10479-011-0841-3"}],"container-title":["IEEE Transactions on Cybernetics"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6221036\/9733099\/09086133.pdf?arnumber=9086133","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,9]],"date-time":"2024-01-09T22:32:27Z","timestamp":1704839547000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9086133\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,3]]},"references-count":65,"journal-issue":{"issue":"3"},"URL":"https:\/\/doi.org\/10.1109\/tcyb.2020.2984489","relation":{},"ISSN":["2168-2267","2168-2275"],"issn-type":[{"value":"2168-2267","type":"print"},{"value":"2168-2275","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,3]]}}}