{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,23]],"date-time":"2026-01-23T12:31:49Z","timestamp":1769171509490,"version":"3.49.0"},"reference-count":62,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"2","license":[{"start":{"date-parts":[[2023,2,1]],"date-time":"2023-02-01T00:00:00Z","timestamp":1675209600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2023,2,1]],"date-time":"2023-02-01T00:00:00Z","timestamp":1675209600000},"content-version":"am","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2023,2,1]],"date-time":"2023-02-01T00:00:00Z","timestamp":1675209600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,2,1]],"date-time":"2023-02-01T00:00:00Z","timestamp":1675209600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100008982","name":"National Science Foundation","doi-asserted-by":"publisher","award":["CNS-1936370"],"award-info":[{"award-number":["CNS-1936370"]}],"id":[{"id":"10.13039\/501100008982","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100008982","name":"National Science Foundation","doi-asserted-by":"publisher","award":["OAC-1917117"],"award-info":[{"award-number":["OAC-1917117"]}],"id":[{"id":"10.13039\/501100008982","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["91846201"],"award-info":[{"award-number":["91846201"]}],"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":["72101079"],"award-info":[{"award-number":["72101079"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Shanghai Data Exchange Cooperative Program","award":["W2021JSZX0052"],"award-info":[{"award-number":["W2021JSZX0052"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Pattern Anal. Mach. Intell."],"published-print":{"date-parts":[[2023,2,1]]},"DOI":"10.1109\/tpami.2022.3163338","type":"journal-article","created":{"date-parts":[[2022,3,29]],"date-time":"2022-03-29T19:48:13Z","timestamp":1648583293000},"page":"1862-1875","source":"Crossref","is-referenced-by-count":15,"title":["Heterogeneous Domain Adaptation With Adversarial Neural Representation Learning: Experiments on E-Commerce and Cybersecurity"],"prefix":"10.1109","volume":"45","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1367-3338","authenticated-orcid":false,"given":"Mohammadreza","family":"Ebrahimi","sequence":"first","affiliation":[{"name":"School of Information Systems and Management, University of South Florida, Tampa, FL, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0260-7589","authenticated-orcid":false,"given":"Yidong","family":"Chai","sequence":"additional","affiliation":[{"name":"School of Management, Hefei University of Technology, Hefei, Anhui, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hao Helen","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Mathematics, University of Arizona, Tucson, AZ, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hsinchun","family":"Chen","sequence":"additional","affiliation":[{"name":"Aritificial Intelligence Lab, University of Arizona, Tucson, AZ, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01237-3_9"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2016.2599532"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2020.2976933"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2017.2786727"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2018.2868854"},{"key":"ref6","first-page":"1989","article-title":"CyCADA: Cycle-consistent adversarial domain adaptation","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Hoffman"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01267-0_38"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1016\/j.patrec.2018.02.011"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2018.09.027"},{"key":"ref10","article-title":"Factorized adversarial networks for unsupervised domain adaptation","author":"Ren","year":"2018"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2018.2868685"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.5555\/2946645.2946704"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.316"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.3156\/jsoft.29.5_177_2"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1186\/s40537-016-0043-6"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2009.191"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2013.50"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2013.274"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/TNN.2010.2091281"},{"key":"ref20","first-page":"1898","article-title":"Flexible transfer learning under support and model shift","volume-title":"Proc. Adv. Neural Informat. Process. Syst.","author":"Wang"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/ICME.2016.7552878"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.421"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.549"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2014.2343216"},{"key":"ref25","first-page":"1095","article-title":"Heterogeneous domain adaptation for multiple classes","volume-title":"Proc. Artif. Intell. Statist.","author":"Zhou"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2013.167"},{"key":"ref27","first-page":"1","article-title":"Efficient learning of domain-invariant image representations","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Hoffman"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46454-1_25"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1016\/j.jpdc.2017.06.003"},{"key":"ref30","first-page":"1627","article-title":"Marginalized denoising autoencoders for domain adaptation","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Chen"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2016.2554549"},{"key":"ref32","volume-title":"Deep Learning","volume":"1","author":"Goodfellow","year":"2016"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/p17-1001"},{"key":"ref34","first-page":"8559","article-title":"Adversarial multiple source domain adaptation","volume-title":"Proc. Adv. Neural Informat. Process. Syst.","author":"Zhao"},{"key":"ref35","first-page":"165","article-title":"Label efficient learning of transferable representations acrosss domains and tasks","volume-title":"Proc. Adv. Neural Informat. Process. Syst.","author":"Luo"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00845"},{"key":"ref37","first-page":"469","article-title":"Coupled generative adversarial networks","volume-title":"Proc. Adv. Neural Informat. Process. Syst.","author":"Liu"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00887"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00517"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1007\/s10994-009-5152-4"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.7551\/mitpress\/7503.003.0022"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-75225-7_5"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/TCI.2018.2840334"},{"key":"ref44","first-page":"2203","article-title":"MMD GAN: Towards deeper understanding of moment matching network","volume-title":"Proc. Adv. Neural Informat. Process. Syst.","author":"Li"},{"key":"ref45","first-page":"513","article-title":"Domain adaptation for large-scale sentiment classification: A deep learning approach","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Glorot"},{"key":"ref46","first-page":"62","article-title":"Domain adaptation by constraining inter-domain variability of latent feature representation","volume-title":"Proc. 49th Annu. Meeting Assoc. Comput. Linguistics, Hum. Lang. Technol.","author":"Titov"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2018.2816981"},{"issue":"Mar","key":"ref48","first-page":"723","article-title":"A kernel two-sample test","volume":"13","author":"Gretton","year":"2012","journal-title":"J. Mach. Learn. Res."},{"key":"ref49","first-page":"1750","article-title":"Kernel choice and classifiability for RKHS embeddings of probability distributions","volume-title":"Proc. Adv. Neural Informat. Process. Syst.","author":"Sriperumbudur"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2013.53"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2011.105"},{"key":"ref52","first-page":"28","article-title":"Learning from multiple partially observed views-an application to multilingual text categorization","volume-title":"Proc. Adv. Neural Informat. Process. Syst.","author":"Amini"},{"key":"ref53","first-page":"222","article-title":"Connecting the dots with landmarks: Discriminatively learning domain-invariant features for unsupervised domain adaptation","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Gong"},{"key":"ref54","first-page":"647","article-title":"DeCAF: A deep convolutional activation feature for generic visual recognition","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Donahue"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1109\/ISI.2018.8587404"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1109\/IRI.2018.00041"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1007\/978-0-387-21606-5"},{"key":"ref58","first-page":"214","article-title":"Wasserstein generative adversarial networks","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Arjovsky"},{"key":"ref59","first-page":"1","article-title":"Minimal-entropy correlation alignment for unsupervised deep domain adaptation","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Morerio"},{"key":"ref60","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":"ref61","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-15939-8_35"},{"key":"ref62","first-page":"2579","article-title":"Visualizing data using t-SNE","volume":"9","author":"Maaten","year":"2008","journal-title":"J. Mach. Learn. Res."}],"container-title":["IEEE Transactions on Pattern Analysis and Machine Intelligence"],"original-title":[],"link":[{"URL":"https:\/\/ieeexplore.ieee.org\/ielam\/34\/10008914\/9744510-aam.pdf","content-type":"application\/pdf","content-version":"am","intended-application":"syndication"},{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/34\/10008914\/09744510.pdf?arnumber=9744510","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,18]],"date-time":"2024-01-18T00:30:18Z","timestamp":1705537818000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9744510\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,2,1]]},"references-count":62,"journal-issue":{"issue":"2"},"URL":"https:\/\/doi.org\/10.1109\/tpami.2022.3163338","relation":{},"ISSN":["0162-8828","2160-9292","1939-3539"],"issn-type":[{"value":"0162-8828","type":"print"},{"value":"2160-9292","type":"electronic"},{"value":"1939-3539","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,2,1]]}}}