{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,17]],"date-time":"2026-02-17T12:02:47Z","timestamp":1771329767054,"version":"3.50.1"},"reference-count":65,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"12","license":[{"start":{"date-parts":[[2020,12,1]],"date-time":"2020-12-01T00:00:00Z","timestamp":1606780800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2020,12,1]],"date-time":"2020-12-01T00:00:00Z","timestamp":1606780800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2020,12,1]],"date-time":"2020-12-01T00:00:00Z","timestamp":1606780800000},"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":["61273295"],"award-info":[{"award-number":["61273295"]}],"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":["61502175"],"award-info":[{"award-number":["61502175"]}],"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":["61503141"],"award-info":[{"award-number":["61503141"]}],"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":["61906069"],"award-info":[{"award-number":["61906069"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003453","name":"Guangdong Natural Science Funds","doi-asserted-by":"publisher","award":["2019A1515011411"],"award-info":[{"award-number":["2019A1515011411"]}],"id":[{"id":"10.13039\/501100003453","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003453","name":"Guangdong Natural Science Funds","doi-asserted-by":"publisher","award":["2019A1515011700"],"award-info":[{"award-number":["2019A1515011700"]}],"id":[{"id":"10.13039\/501100003453","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"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Neural Netw. Learning Syst."],"published-print":{"date-parts":[[2020,12]]},"DOI":"10.1109\/tnnls.2020.2964790","type":"journal-article","created":{"date-parts":[[2020,1,24]],"date-time":"2020-01-24T21:45:14Z","timestamp":1579902314000},"page":"5204-5218","source":"Crossref","is-referenced-by-count":48,"title":["Subspace Distribution Adaptation Frameworks for Domain Adaptation"],"prefix":"10.1109","volume":"31","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3692-0728","authenticated-orcid":false,"given":"Sentao","family":"Chen","sequence":"first","affiliation":[]},{"given":"Le","family":"Han","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0560-472X","authenticated-orcid":false,"given":"Xiaolan","family":"Liu","sequence":"additional","affiliation":[]},{"given":"Zongyao","family":"He","sequence":"additional","affiliation":[]},{"given":"Xiaowei","family":"Yang","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref39","article-title":"Deep domain confusion: Maximizing for domain invariance","author":"tzeng","year":"2014","journal-title":"arXiv 1412 3474"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2012.75"},{"key":"ref33","first-page":"1010","article-title":"Correcting covariate shift with the Frank-Wolfe algorithm","author":"wen","year":"2015","journal-title":"Proc IJCAI"},{"key":"ref32","first-page":"1391","article-title":"A least-squares approach to direct importance estimation","volume":"10","author":"kanamori","year":"2009","journal-title":"J Mach Learn Res"},{"key":"ref31","first-page":"1433","article-title":"Direct importance estimation with model selection and its application to covariate shift adaptation","author":"sugiyama","year":"2008","journal-title":"Proc NIPS"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/ICDMW.2013.117"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2009.126"},{"key":"ref36","first-page":"53","article-title":"Frustratingly easy domain adaptation","author":"daum\u00e9","year":"2007","journal-title":"Proc Workshop Domain Adapt Nat Lang Process"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.3115\/1610075.1610094"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2016.0095"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2005.177"},{"key":"ref62","first-page":"985","article-title":"Covariate shift adaptation by importance weighted cross validation","volume":"8","author":"sugiyama","year":"2007","journal-title":"J Mach Learn Res"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2019.2899037"},{"key":"ref63","first-page":"1","article-title":"Statistical comparisons of classifiers over multiple data sets","volume":"7","author":"dem\u0161ar","year":"2006","journal-title":"J Mach Learn Res"},{"key":"ref28","author":"vapnik","year":"1998","journal-title":"Statistical Learning Theory"},{"key":"ref64","first-page":"731","article-title":"Information, divergence and risk for binary experiments","volume":"12","author":"reid","year":"2011","journal-title":"J Mach Learn Res"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2013.368"},{"key":"ref65","doi-asserted-by":"publisher","DOI":"10.1017\/CBO9780511804441"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1145\/1015330.1015425"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2018.2874567"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2014.2330900"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2016.2547397"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1016\/S0378-3758(00)00115-4"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2016.2616119"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/TNN.2010.2091281"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2009.07.007"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2014.183"},{"key":"ref25","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":"ref50","first-page":"463","article-title":"Rademacher and Gaussian complexities: Risk bounds and structural results","volume":"3","author":"bartlett","year":"2002","journal-title":"J Mach Learn Res"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33014122"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.3115\/1218955.1218990"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1145\/1281192.1281218"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2018.2868709"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1007\/s00186-007-0161-1"},{"key":"ref55","author":"nocedal","year":"2006","journal-title":"Numerical Optimization"},{"key":"ref54","first-page":"304","article-title":"Linking losses for density ratio and class-probability estimation","author":"menon","year":"2016","journal-title":"Proc ICML"},{"key":"ref53","first-page":"1375","article-title":"Back to the future: Radial basis function networks revisited","author":"que","year":"2016","journal-title":"Proc AISTATS"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2016.2599532"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2019.01.025"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2016.2538282"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00887"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1007\/s10994-016-5577-5"},{"key":"ref13","first-page":"1","article-title":"Domain-adversarial training of neural networks","volume":"17","author":"ganin","year":"2016","journal-title":"J Mach Learn Res"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00362"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2014.2308325"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2019.2935608"},{"key":"ref17","first-page":"601","article-title":"Correcting sample selection bias by unlabeled data","volume":"2007","author":"huang","year":"0","journal-title":"Proc NIPS"},{"key":"ref18","first-page":"2137","article-title":"Discriminative learning under covariate shift","volume":"10","author":"bickel","year":"2009","journal-title":"J Mach Learn Res"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2011.09.016"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2018.2868854"},{"key":"ref3","first-page":"5943","article-title":"Feature-level domain adaptation","volume":"17","author":"kouw","year":"2016","journal-title":"J Mach Learn Res"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.547"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2016.2615921"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2018.2863240"},{"key":"ref7","first-page":"2795","article-title":"Unsupervised domain adaptation with distribution matching machines","author":"cao","year":"2018","journal-title":"Proc AAAI"},{"key":"ref49","article-title":"Domain adaptation: Learning bounds and algorithms","author":"mansour","year":"2009","journal-title":"Proc Conf Learn Theory"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2017.04.011"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2019.2944455"},{"key":"ref45","first-page":"2066","article-title":"Geodesic flow kernel for unsupervised domain adaptation","author":"gong","year":"2012","journal-title":"Proc IEEE Conf Comput Vis Pattern Recognit"},{"key":"ref48","first-page":"137","article-title":"Analysis of representations for domain adaptation","author":"ben-david","year":"2007","journal-title":"Proc NIPS"},{"key":"ref47","first-page":"2058","article-title":"Return of frustratingly easy domain adaptation","author":"sun","year":"2016","journal-title":"Proc AAAI"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2019.2935384"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00473"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2011.6126344"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00309"}],"container-title":["IEEE Transactions on Neural Networks and Learning Systems"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/5962385\/9273274\/08968742.pdf?arnumber=8968742","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,4,27]],"date-time":"2022-04-27T17:19:38Z","timestamp":1651079978000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8968742\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,12]]},"references-count":65,"journal-issue":{"issue":"12"},"URL":"https:\/\/doi.org\/10.1109\/tnnls.2020.2964790","relation":{},"ISSN":["2162-237X","2162-2388"],"issn-type":[{"value":"2162-237X","type":"print"},{"value":"2162-2388","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,12]]}}}