{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2022,3,30]],"date-time":"2022-03-30T23:53:25Z","timestamp":1648684405443},"reference-count":27,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"6","license":[{"start":{"date-parts":[[2016,6,1]],"date-time":"2016-06-01T00:00:00Z","timestamp":1464739200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Neural Netw. Learning Syst."],"published-print":{"date-parts":[[2016,6]]},"DOI":"10.1109\/tnnls.2015.2497275","type":"journal-article","created":{"date-parts":[[2016,1,28]],"date-time":"2016-01-28T19:32:23Z","timestamp":1454009543000},"page":"1322-1332","source":"Crossref","is-referenced-by-count":2,"title":["Learning in Variable-Dimensional Spaces"],"prefix":"10.1109","volume":"27","author":[{"given":"Michelangelo","family":"Diligenti","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Marco","family":"Gori","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Claudio","family":"Sacca","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref10","author":"adams","year":"2003","journal-title":"Sobolev Spaces"},{"key":"ref11","first-page":"49","article-title":"Sur les probl&#x00E8;mes aux d&#x00E9;riv&#x00E9;s partielles et leur signification physique","volume":"13","author":"hadamard","year":"1902","journal-title":"Princeton Univ Bull"},{"key":"ref12","article-title":"A theory of networks for approximation and learning","author":"poggio","year":"1989"},{"key":"ref13","author":"tikhonov","year":"1977","journal-title":"Solutions of Ill-posed Problems"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1007\/BF01437407"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1137\/1.9781611970128"},{"key":"ref16","article-title":"From regularization operators to support vector kernels","author":"smola","year":"1998","journal-title":"Advances in neural information processing systems"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1016\/S0893-6080(98)00032-X"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1162\/NECO_a_00417"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1023\/A:1018946025316"},{"key":"ref4","doi-asserted-by":"crossref","first-page":"101","DOI":"10.1613\/jair.1872","article-title":"Domain adaptation for statistical classifiers","volume":"26","author":"daum\u00e9","year":"2006","journal-title":"J Artif Intell Res"},{"key":"ref27","first-page":"25","article-title":"A spectral regularization framework for multi-task structure learning","volume":"20","author":"argyriou","year":"2007","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2013.73"},{"key":"ref6","first-page":"126","article-title":"A regularization framework for learning from graph data","author":"zhou","year":"2004","journal-title":"Proc ICML Workshop Statistical Relational Learning"},{"key":"ref5","first-page":"137","article-title":"Analysis of representations for domain adaptation","author":"ben-david","year":"2007","journal-title":"Advances in neural information processing systems"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1145\/1052934.1052938"},{"key":"ref7","first-page":"684","article-title":"Learning Web page scores by error back-propagation","author":"diligenti","year":"2007","journal-title":"Proc IJCAI"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2014.2361866"},{"key":"ref9","author":"sch\u00f6lkopf","year":"2002","journal-title":"Learning with kernels"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1162\/NECO_a_00686"},{"key":"ref20","first-page":"615","article-title":"Learning multiple tasks with kernel methods","volume":"6","author":"evgeniou","year":"2005","journal-title":"J Mach Learn Res"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1007\/s10994-011-5243-x"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-78652-8_1"},{"key":"ref24","author":"gelfand","year":"1963","journal-title":"Calculus of Variations"},{"key":"ref23","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":"ref26","doi-asserted-by":"publisher","DOI":"10.1162\/0899766052530802"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1007\/BF00126430"}],"container-title":["IEEE Transactions on Neural Networks and Learning Systems"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/5962385\/7470313\/07394191.pdf?arnumber=7394191","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,1,12]],"date-time":"2022-01-12T16:45:04Z","timestamp":1642005904000},"score":1,"resource":{"primary":{"URL":"http:\/\/ieeexplore.ieee.org\/document\/7394191\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,6]]},"references-count":27,"journal-issue":{"issue":"6"},"URL":"https:\/\/doi.org\/10.1109\/tnnls.2015.2497275","relation":{},"ISSN":["2162-237X","2162-2388"],"issn-type":[{"value":"2162-237X","type":"print"},{"value":"2162-2388","type":"electronic"}],"subject":[],"published":{"date-parts":[[2016,6]]}}}