{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,5]],"date-time":"2025-11-05T11:16:52Z","timestamp":1762341412376,"version":"3.37.3"},"reference-count":61,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"2","license":[{"start":{"date-parts":[[2021,2,1]],"date-time":"2021-02-01T00:00:00Z","timestamp":1612137600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2021,2,1]],"date-time":"2021-02-01T00:00:00Z","timestamp":1612137600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2021,2,1]],"date-time":"2021-02-01T00:00:00Z","timestamp":1612137600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100002920","name":"Hong Kong Research Grants Council","doi-asserted-by":"publisher","award":["CUHK14306316","CUHK14301718"],"award-info":[{"award-number":["CUHK14306316","CUHK14301718"]}],"id":[{"id":"10.13039\/501100002920","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100007567","name":"City University of Hong Kong","doi-asserted-by":"publisher","award":["9380101"],"award-info":[{"award-number":["9380101"]}],"id":[{"id":"10.13039\/100007567","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Collaborative Research Fund","award":["C1007-15G","AoE\/M-05\/12"],"award-info":[{"award-number":["C1007-15G","AoE\/M-05\/12"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["11671002"],"award-info":[{"award-number":["11671002"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004853","name":"The Chinese University of Hong Kong","doi-asserted-by":"publisher","award":["CUHK DAG 4053342"],"award-info":[{"award-number":["CUHK DAG 4053342"]}],"id":[{"id":"10.13039\/501100004853","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002920","name":"Research Grants Council","doi-asserted-by":"publisher","award":["14300219"],"award-info":[{"award-number":["14300219"]}],"id":[{"id":"10.13039\/501100002920","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"NSFC\/RGC","doi-asserted-by":"publisher","award":["N_CUHK 415\/19"],"award-info":[{"award-number":["N_CUHK 415\/19"]}],"id":[{"id":"10.13039\/501100001809","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":[[2021,2]]},"DOI":"10.1109\/tnnls.2020.2979607","type":"journal-article","created":{"date-parts":[[2020,4,10]],"date-time":"2020-04-10T20:17:52Z","timestamp":1586549872000},"page":"853-867","source":"Crossref","is-referenced-by-count":20,"title":["Probabilistic Semi-Supervised Learning via Sparse Graph Structure Learning"],"prefix":"10.1109","volume":"32","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2658-4262","authenticated-orcid":false,"given":"Li","family":"Wang","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0910-4685","authenticated-orcid":false,"given":"Raymond","family":"Chan","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0688-202X","authenticated-orcid":false,"given":"Tieyong","family":"Zeng","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2015.2415497"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2007.190672"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-15880-3_42"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1145\/2505515.2505559"},{"key":"ref31","first-page":"912","article-title":"Semi-supervised learning using Gaussian fields and harmonic functions","author":"zhu","year":"2003","journal-title":"Proc 20th Int Conf Mach Learn (ICML)"},{"key":"ref30","first-page":"321","article-title":"Learning with local and global consistency","author":"zhou","year":"2004","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1137\/1.9781611972771.73"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2012.09.010"},{"key":"ref35","first-page":"1","article-title":"Parameter-free spectral kernel learning","author":"mao","year":"2010","journal-title":"Proc 26th Conf Uncertainty Artif Intell"},{"key":"ref34","first-page":"2491","article-title":"SimpleMKL","volume":"9","author":"rakotomamonjy","year":"2008","journal-title":"J Mach Learn Res"},{"key":"ref60","first-page":"45","article-title":"Support vector machine active learning with applications to text classification","volume":"2","author":"tong","year":"2001","journal-title":"J Mach Learn Res"},{"journal-title":"Columbia Object Image Library (COIL-20)","year":"1996","author":"nene","key":"ref61"},{"key":"ref28","first-page":"2579","article-title":"Visualizing data using t-SNE","volume":"9","author":"van der maaten","year":"2008","journal-title":"J Mach Learn Res"},{"key":"ref27","article-title":"Discovering structure by learning sparse graph","author":"lake","year":"2010","journal-title":"Proc 33rd Annu Cogn Sci Conf"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1145\/1015330.1015345"},{"journal-title":"Semi-supervised learning literature survey","year":"2005","author":"zhu","key":"ref2"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TNN.2009.2015974"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2019.2893956"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/TBDATA.2018.2797977"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2016.2598671"},{"key":"ref24","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":"ref23","article-title":"Robust triple-matrix-recovery-based auto-weighted label propagation for classification","author":"zhang","year":"2019","journal-title":"arXiv 1911 08678"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2009.2038764"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1007\/s10462-010-9200-z"},{"key":"ref50","doi-asserted-by":"crossref","DOI":"10.7551\/mitpress\/4175.001.0001","author":"scholkopf","year":"2001","journal-title":"Learning With Kernels Support Vector Machines Regularization Optimization and Beyond"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1007\/BFb0020217"},{"key":"ref59","first-page":"289","article-title":"Intrinsic dimensionality estimation of submanifolds in R?","author":"hein","year":"2005","journal-title":"Proc 22nd Int Conf Mach Learn"},{"key":"ref58","first-page":"6","article-title":"Nonlinear dimensionality reduction by semidefinite programming and kernel matrix factorization","volume":"2","author":"weinberger","year":"2005","journal-title":"Proc AISTATS"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2014.2300478"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1007\/s10915-017-0429-4"},{"key":"ref55","first-page":"3311","article-title":"Semi-supervised learning with measure propagation","volume":"12","author":"subramanya","year":"2011","journal-title":"J Mach Learn Res"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1038\/nmeth.4402"},{"key":"ref53","first-page":"536","article-title":"Exploring latent structures of Alzheimer’s disease via structure learning","author":"zhu","year":"2018","journal-title":"Proc IEEE 15th Int Symp Biomed Imag (ISBI)"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1145\/1961189.1961199"},{"key":"ref10","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":"ref11","first-page":"55","article-title":"Sparse manifold clustering and embedding","author":"elhamifar","year":"2011","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2017.2727526"},{"key":"ref12","first-page":"217","article-title":"When is nearest neighbor meaningful?","author":"beyer","year":"1999","journal-title":"Proc Int Conf Database Theory"},{"key":"ref13","first-page":"679","article-title":"Large graph construction for scalable semi-supervised learning","author":"liu","year":"2010","journal-title":"Proc 27th Int Conf Mach Learn (ICML)"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2016.2535367"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2017.2654445"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2018.2869875"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2017.09.043"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2016.02.001"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2016.07.042"},{"key":"ref4","first-page":"200","article-title":"Transductive inference for text classification using support vector machines","volume":"99","author":"joachims","year":"1999","journal-title":"Proc ICML"},{"key":"ref3","first-page":"319","article-title":"High-performance semi-supervised learning using discriminatively constrained generative models","author":"druck","year":"2010","journal-title":"Proc 27th Int Conf Mach Learn (ICML)"},{"journal-title":"Learning From Labeled and Unlabeled Data With Label Propagation","year":"2002","author":"xiaojin","key":"ref6"},{"key":"ref5","first-page":"1687","article-title":"Large scale transductive SVMs","volume":"7","author":"collobert","year":"2006","journal-title":"J Mach Learn Res"},{"key":"ref8","doi-asserted-by":"crossref","first-page":"639","DOI":"10.1007\/978-3-642-35289-8_34","article-title":"Deep learning via semi-supervised embedding","author":"weston","year":"2012","journal-title":"Neural Networks Tricks of the Trade"},{"key":"ref7","first-page":"290","article-title":"Transductive learning via spectral graph partitioning","author":"joachims","year":"2003","journal-title":"Proc 20th Int Conf Mach Learn (ICML)"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1137\/0916069"},{"key":"ref9","first-page":"1","article-title":"Revisiting semi-supervised learning with graph embeddings","author":"yang","year":"2016","journal-title":"Proc 33rd Int Conf Mach Learn"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1007\/s10994-016-5602-8"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/34.908974"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1561\/2200000016"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1017\/CBO9780511804441"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2012.2207397"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2017.2703120"},{"key":"ref44","first-page":"1","article-title":"Latent smooth skeleton embedding","author":"wang","year":"2017","journal-title":"Proc 31st AAAI Conf Artif Intell"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/TSMCB.2009.2034632"}],"container-title":["IEEE Transactions on Neural Networks and Learning Systems"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/5962385\/9346113\/09063663.pdf?arnumber=9063663","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,8,3]],"date-time":"2024-08-03T20:32:23Z","timestamp":1722717143000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9063663\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,2]]},"references-count":61,"journal-issue":{"issue":"2"},"URL":"https:\/\/doi.org\/10.1109\/tnnls.2020.2979607","relation":{},"ISSN":["2162-237X","2162-2388"],"issn-type":[{"type":"print","value":"2162-237X"},{"type":"electronic","value":"2162-2388"}],"subject":[],"published":{"date-parts":[[2021,2]]}}}