{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,11]],"date-time":"2026-03-11T22:59:22Z","timestamp":1773269962070,"version":"3.50.1"},"reference-count":52,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"12","license":[{"start":{"date-parts":[[2021,12,1]],"date-time":"2021-12-01T00:00:00Z","timestamp":1638316800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2021,12,1]],"date-time":"2021-12-01T00:00:00Z","timestamp":1638316800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2021,12,1]],"date-time":"2021-12-01T00:00:00Z","timestamp":1638316800000},"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","award":["61906069"],"award-info":[{"award-number":["61906069"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100021171","name":"Basic and Applied Basic Research Foundation of Guangdong Province","doi-asserted-by":"publisher","award":["2019A1515011411"],"award-info":[{"award-number":["2019A1515011411"]}],"id":[{"id":"10.13039\/501100021171","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100021171","name":"Basic and Applied Basic Research Foundation of Guangdong Province","doi-asserted-by":"publisher","award":["2019A1515011700"],"award-info":[{"award-number":["2019A1515011700"]}],"id":[{"id":"10.13039\/501100021171","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002858","name":"China Postdoctoral Science Foundation","doi-asserted-by":"publisher","award":["2019M662912"],"award-info":[{"award-number":["2019M662912"]}],"id":[{"id":"10.13039\/501100002858","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Science and Technology Program of Guangzhou","award":["202002030355"],"award-info":[{"award-number":["202002030355"]}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["2019MS088"],"award-info":[{"award-number":["2019MS088"]}],"id":[{"id":"10.13039\/501100012226","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":[[2021,12]]},"DOI":"10.1109\/tnnls.2020.3027364","type":"journal-article","created":{"date-parts":[[2020,10,15]],"date-time":"2020-10-15T19:28:42Z","timestamp":1602790122000},"page":"5708-5722","source":"Crossref","is-referenced-by-count":25,"title":["Semi-Supervised Domain Adaptation via Asymmetric Joint Distribution Matching"],"prefix":"10.1109","volume":"32","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3692-0728","authenticated-orcid":false,"given":"Sentao","family":"Chen","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6937-6300","authenticated-orcid":false,"given":"Mehrtash","family":"Harandi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaona","family":"Jin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaowei","family":"Yang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2013.274"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2018.2839528"},{"key":"ref33","first-page":"1","article-title":"Robust PCA by manifold optimization","volume":"19","author":"zhang","year":"2018","journal-title":"J Mach Learn Res"},{"key":"ref32","author":"vapnik","year":"1998","journal-title":"Statistical Learning Theory"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2018.2872043"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2013.01.012"},{"key":"ref37","first-page":"299","article-title":"Classes of kernels for machine learning: A statistics perspective","volume":"2","author":"genton","year":"2001","journal-title":"J Mach Learn Res"},{"key":"ref36","first-page":"145","article-title":"Transfer learning by distribution matching for targeted advertising","author":"bickel","year":"2009","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref35","author":"wasserman","year":"2013","journal-title":"All of Statistics A Concise Course in Statistical Inference"},{"key":"ref34","first-page":"1","article-title":"Distribution-matching embedding for visual domain adaptation","volume":"17","author":"baktashmotlagh","year":"2016","journal-title":"J Mach Learn Res"},{"key":"ref28","first-page":"819","article-title":"Domain adaptation under target and conditional shift","author":"zhang","year":"2013","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref27","first-page":"1640","article-title":"Conditional adversarial domain adaptation","author":"long","year":"2018","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1162\/NECO_a_00442"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2016.2599532"},{"key":"ref1","author":"jiang","year":"2008","journal-title":"A Literature Survey on Domain Adaptation of Statistical Classifiers"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2019.2929421"},{"key":"ref22","author":"absil","year":"2009","journal-title":"Optimization Algorithms on Matrix Manifolds"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1016\/S0378-3758(00)00115-4"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.468"},{"key":"ref23","first-page":"723","article-title":"A kernel two-sample test","volume":"13","author":"gretton","year":"2012","journal-title":"J Mach Learn Res"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.316"},{"key":"ref25","first-page":"1","article-title":"Domain-adversarial training of neural networks","volume":"17","author":"ganin","year":"2016","journal-title":"J Mach Learn Res"},{"key":"ref50","first-page":"1","article-title":"Adversarial dropout regularization","author":"saito","year":"2018","journal-title":"Proc Int Conf Learn Represent"},{"key":"ref51","first-page":"529","article-title":"Semi-supervised learning by entropy minimization","author":"grandvalet","year":"2005","journal-title":"Proc Adv Neural Inf Process Syst (NIPS)"},{"key":"ref52","author":"petersen","year":"2012","journal-title":"The Matrix Cookbook"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2019.2944455"},{"key":"ref11","first-page":"53","article-title":"Frustratingly easy semi-supervised domain adaptation","author":"daume","year":"2010","journal-title":"Proc Workshop Domain Adaptation Natural Lang Process"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2018.2819503"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00362"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2018.2866846"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/TNN.2010.2091281"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2014.2308325"},{"key":"ref16","first-page":"2839","article-title":"Domain adaptation with conditional transferable components","author":"gong","year":"2016","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2019.2935608"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-013-0689-x"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298826"},{"key":"ref4","first-page":"1","article-title":"Efficient learning of domain-invariant image representations","author":"hoffman","year":"2013","journal-title":"Proc Int Conf Learn Represent"},{"key":"ref3","first-page":"2208","article-title":"Deep transfer learning with joint adaptation networks","author":"long","year":"2017","journal-title":"Proc 34th Int Conf Mach Learn"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00814"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33014106"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.421"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2019.2899037"},{"key":"ref49","article-title":"L2-constrained softmax loss for discriminative face verification","author":"ranjan","year":"2017","journal-title":"arXiv 1703 09507"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2017.04.011"},{"key":"ref46","first-page":"1097","article-title":"ImageNet classification with deep convolutional neural networks","author":"krizhevsky","year":"2012","journal-title":"Proc Adv Neural Inf Process Syst (NIPS)"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2018.2874567"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2016.2615921"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2013.368"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2014.318"},{"key":"ref41","doi-asserted-by":"crossref","DOI":"10.7551\/mitpress\/4175.001.0001","author":"sch\u00f6lkopf","year":"2001","journal-title":"Learning With Kernels Support Vector Machines Regularization Optimization and Beyond"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.572"},{"key":"ref43","first-page":"213","article-title":"Adapting visual category models to new domains","author":"saenko","year":"2010","journal-title":"Proc Eur Conf Comput Vis"}],"container-title":["IEEE Transactions on Neural Networks and Learning Systems"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/5962385\/9629429\/09225701.pdf?arnumber=9225701","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,8,15]],"date-time":"2024-08-15T23:41:02Z","timestamp":1723765262000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9225701\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,12]]},"references-count":52,"journal-issue":{"issue":"12"},"URL":"https:\/\/doi.org\/10.1109\/tnnls.2020.3027364","relation":{},"ISSN":["2162-237X","2162-2388"],"issn-type":[{"value":"2162-237X","type":"print"},{"value":"2162-2388","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,12]]}}}