{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,8]],"date-time":"2026-01-08T18:22:10Z","timestamp":1767896530339,"version":"3.49.0"},"reference-count":47,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. on Image Process."],"published-print":{"date-parts":[[2021]]},"DOI":"10.1109\/tip.2021.3071688","type":"journal-article","created":{"date-parts":[[2021,4,14]],"date-time":"2021-04-14T00:20:01Z","timestamp":1618359601000},"page":"4384-4394","source":"Crossref","is-referenced-by-count":4,"title":["Learning Multi-Modal Nonlinear Embeddings: Performance Bounds and an Algorithm"],"prefix":"10.1109","volume":"30","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9305-706X","authenticated-orcid":false,"given":"Semih","family":"Kaya","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5491-2588","authenticated-orcid":false,"given":"Elif","family":"Vural","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/ICIP.2019.8803196"},{"key":"ref38","doi-asserted-by":"crossref","first-page":"55","DOI":"10.1016\/j.patcog.2018.10.006","article-title":"Nonlinear supervised dimensionality reduction via smooth regular embeddings","volume":"87","author":"\u00f6rnek","year":"2019","journal-title":"Pattern Recognit"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2019.2952707"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2019.2934576"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2018.2881928"},{"key":"ref30","first-page":"2601","article-title":"MDL-CW: A multimodal deep learning framework with cross weights","author":"rastegar","year":"2016","journal-title":"Proc IEEE Conf Comp Vis Pattern Recognit"},{"key":"ref37","first-page":"1","article-title":"A study of the classification of low-dimensional data with supervised manifold learning","volume":"18","author":"vural","year":"2018","journal-title":"J Mach Learn Res"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2015.2417578"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2016.09.008"},{"key":"ref34","first-page":"2921","article-title":"Multi-view clustering via deep matrix factorization","author":"zhao","year":"2017","journal-title":"Proc 21st AAAI Conf Artif Intel"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1145\/1015330.1015350"},{"key":"ref40","article-title":"Learning multi-modal nonlinear embeddings: Performance bounds and an algorithm","author":"kaya","year":"2020","journal-title":"arXiv 2006 02330"},{"key":"ref11","first-page":"908","article-title":"Semi-supervised regression with co-training","author":"zhou","year":"2005","journal-title":"Proc 19th Int Joint Conf Artif Intell"},{"key":"ref12","first-page":"2649","article-title":"Bayesian co-training","volume":"12","author":"yu","year":"2011","journal-title":"J Mach Learn Res"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/CIBIM.2014.7015447"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/ICTAI.2017.00098"},{"key":"ref15","first-page":"823","article-title":"Cluster canonical correlation analysis","author":"rasiwasia","year":"2014","journal-title":"Proc 17th Int Conf Artif Intell Statist"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.466"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-013-0658-4"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2015.2435740"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1145\/2775109"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/TSMCB.2009.2039566"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2016.2519449"},{"key":"ref27","first-page":"14848","article-title":"Generalized matrix means for semi-supervised learning with multilayer graphs","author":"mercado","year":"2019","journal-title":"Proc Adv Neur Inf Process Syst"},{"key":"ref3","first-page":"689","article-title":"Multimodal deep learning","author":"ngiam","year":"2011","journal-title":"Proc 28th Int Conf Mach Learn"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1145\/279943.279962"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2018.2831454"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1145\/2647868.2654902"},{"key":"ref8","first-page":"396","article-title":"The Rademacher complexity of co-regularized kernel classes","volume":"2","author":"rosenberg","year":"2007","journal-title":"Proc Artif Intell Statist"},{"key":"ref7","first-page":"375","article-title":"PAC generalization bounds for co-training","author":"dasgupta","year":"2001","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2012.6247923"},{"key":"ref9","doi-asserted-by":"crossref","first-page":"209","DOI":"10.1007\/978-3-642-25856-5_16","article-title":"Multi-view Laplacian support vector machines","volume":"7121","author":"sun","year":"2011","journal-title":"Proc Adv Data Mining Appl"},{"key":"ref1","article-title":"A survey on multi-view learning","author":"xu","year":"2013","journal-title":"arXiv 1304 5634"},{"key":"ref46","article-title":"A comprehensive survey on cross-modal retrieval","author":"wang","year":"2016","journal-title":"arXiv 1607 06215"},{"key":"ref20","first-page":"1882","article-title":"Intra-view and inter-view supervised correlation analysis for multi-view feature learning","author":"jing","year":"2014","journal-title":"Proc 28th AAAI Conf Artif Intell"},{"key":"ref45","first-page":"993","article-title":"Latent Dirichlet allocation","volume":"3","author":"blei","year":"2003","journal-title":"J Mach Learn Res"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2015.2502248"},{"key":"ref47","author":"everingham","year":"0","journal-title":"The PASCAL Visual Object Classes Challenge 2007 (VOC2007) Results"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2017.2742705"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2017.2723841"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1016\/j.imavis.2009.08.002"},{"key":"ref41","year":"2021","journal-title":"The MIT-CBCL Face Recognition Database"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2017.01.035"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1145\/1873951.1873987"},{"key":"ref26","first-page":"67","article-title":"Combining graph Laplacians for semi-supervised learning","author":"argyriou","year":"2005","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2018\/131"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2015.2505311"}],"container-title":["IEEE Transactions on Image Processing"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/83\/9263394\/09403995.pdf?arnumber=9403995","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,10]],"date-time":"2022-05-10T14:51:00Z","timestamp":1652194260000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9403995\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"references-count":47,"URL":"https:\/\/doi.org\/10.1109\/tip.2021.3071688","relation":{},"ISSN":["1057-7149","1941-0042"],"issn-type":[{"value":"1057-7149","type":"print"},{"value":"1941-0042","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021]]}}}