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In the first one, a cross-domain Mahalanobis distance is learned by combining three goals: reducing the distribution difference between different domains, preserving the geometry of target domain data, and aligning the geometry of source domain data with label information. Furthermore, we devote our efforts to solving complex domain adaptation problems and go beyond linear cross-domain metric learning by extending the first method to a multiple kernel learning framework. A convex combination of multiple kernels and a linear transformation are adaptively learned in a single optimization, which greatly benefits the exploration of prior knowledge and the description of data characteristics. Comprehensive experiments in three real-world applications (face recognition, text classification, and object categorization) verify that the proposed methods outperform state-of-the-art metric learning and domain adaptation methods. <\/jats:p>","DOI":"10.1162\/neco_a_01053","type":"journal-article","created":{"date-parts":[[2018,1,18]],"date-time":"2018-01-18T00:39:05Z","timestamp":1516235945000},"page":"820-855","source":"Crossref","is-referenced-by-count":3,"title":["Cross-Domain Metric and Multiple Kernel Learning Based on Information Theory"],"prefix":"10.1162","volume":"30","author":[{"given":"Wei","family":"Wang","sequence":"first","affiliation":[{"name":"Institute of Software, Chinese Academy of Sciences, Beijing 100190, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hao","family":"Wang","sequence":"additional","affiliation":[{"name":"360 Search Lab, Qihoo, Beijing 100016, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chen","family":"Zhang","sequence":"additional","affiliation":[{"name":"Institute of Software, Chinese Academy of Sciences, Beijing 100190, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yang","family":"Gao","sequence":"additional","affiliation":[{"name":"Institute of Software, Chinese Academy of Sciences, Beijing 100190, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"281","reference":[{"key":"B1","doi-asserted-by":"publisher","DOI":"10.1145\/1015330.1015424"},{"key":"B2","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2013.100"},{"key":"B3","doi-asserted-by":"publisher","DOI":"10.1109\/34.598228"},{"key":"B4","author":"Berg A.","year":"2012","journal-title":"ImageNet large scale visual recognition challenge 2012"},{"key":"B5","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2001.990529"},{"issue":"2","key":"B6","doi-asserted-by":"crossref","first-page":"202","DOI":"10.1137\/S0036144596306782","volume":"40","author":"Bonnaus J. 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