{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,16]],"date-time":"2025-10-16T06:55:07Z","timestamp":1760597707664,"version":"3.37.3"},"reference-count":37,"publisher":"Springer Science and Business Media LLC","issue":"2-3","license":[{"start":{"date-parts":[[2016,8,1]],"date-time":"2016-08-01T00:00:00Z","timestamp":1470009600000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Mach Learn"],"published-print":{"date-parts":[[2016,9]]},"DOI":"10.1007\/s10994-016-5577-5","type":"journal-article","created":{"date-parts":[[2016,8,1]],"date-time":"2016-08-01T12:48:33Z","timestamp":1470055713000},"page":"315-336","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Interpretable domain adaptation via optimization over the Stiefel manifold"],"prefix":"10.1007","volume":"104","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1690-0540","authenticated-orcid":false,"given":"Christian","family":"P\u00f6litz","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wouter","family":"Duivesteijn","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Katharina","family":"Morik","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2016,8,1]]},"reference":[{"key":"5577_CR1","doi-asserted-by":"crossref","DOI":"10.1515\/9781400830244","volume-title":"Optimization algorithms on matrix manifolds","author":"PA Absil","year":"2008","unstructured":"Absil, P. A., Mahony, R. E., & Sepulchre, R. (2008). Optimization algorithms on matrix manifolds. Princeton: Princeton University Press."},{"key":"5577_CR2","doi-asserted-by":"crossref","unstructured":"Baktashmotlagh, M., Harandi, M., Lovell, B., Salzmann, M. (2013). Unsupervised domain adaptation by domain invariant projection. In ICCV 2013.","DOI":"10.1109\/ICCV.2013.100"},{"key":"5577_CR3","doi-asserted-by":"crossref","unstructured":"Balzano, L., Nowak, R., Recht, B. (2010). Online identification and tracking of subspaces from highly incomplete information. In Proceedings of Allerton.","DOI":"10.1109\/ALLERTON.2010.5706976"},{"issue":"1\u20132","key":"5577_CR4","doi-asserted-by":"crossref","first-page":"151","DOI":"10.1007\/s10994-009-5152-4","volume":"79","author":"S Ben-David","year":"2010","unstructured":"Ben-David, S., Blitzer, J., Crammer, K., Kulesza, A., Pereira, F., & Vaughan, J. W. (2010). A theory of learning from different domains. Machine Learning, 79(1\u20132), 151\u2013175.","journal-title":"Machine Learning"},{"key":"5577_CR5","first-page":"137","volume-title":"NIPS","author":"S Ben-David","year":"2006","unstructured":"Ben-David, S., Blitzer, J., Crammer, K., & Pereira, F. (2006). Analysis of representations for domain adaptation. In B. Sch\u00f6lkopf, J. Platt, & T. Hoffman (Eds.), NIPS (pp. 137\u2013144). Cambridge: MIT Press."},{"key":"5577_CR6","first-page":"2137","volume":"10","author":"S Bickel","year":"2009","unstructured":"Bickel, S., Br\u00fcckner, M., & Scheffer, T. (2009). Discriminative learning under covariate shift. Journal of Machine Learning Research, 10, 2137\u20132155.","journal-title":"Journal of Machine Learning Research"},{"key":"5577_CR7","unstructured":"Blitzer, J., Dredze, M., Pereira, F. (2007). Biographies, Bollywood, boom-boxes and blenders: Domain adaptation for sentiment classification. In Proceedings of the 45th Annual Meeting of the Association of Computational Linguistics (pp. 440\u2013447)."},{"issue":"9","key":"5577_CR8","doi-asserted-by":"crossref","first-page":"2217","DOI":"10.1109\/TAC.2013.2254619","volume":"58","author":"S Bonnabel","year":"2013","unstructured":"Bonnabel, S. (2013). Stochastic gradient descent on Riemannian manifolds. IEEE Transactions on Automatic Control, 58(9), 2217\u20132229.","journal-title":"IEEE Transactions on Automatic Control"},{"key":"5577_CR9","doi-asserted-by":"crossref","unstructured":"Bottou, L. (1999). On-line learning and stochastic approximations. In D. Saad (Ed.), On-line learning in neural networks (pp. 9\u201342). New York, NY: Cambridge University Press.","DOI":"10.1017\/CBO9780511569920.003"},{"key":"5577_CR10","unstructured":"Boumal, N., Mishra, B., Absil, P. A., Sepulchre, R. (2013). Manopt: A Matlab toolbox for optimization on manifolds. arXiv preprint arXiv:1308.5200 ."},{"issue":"4","key":"5577_CR11","doi-asserted-by":"publisher","first-page":"18:1","DOI":"10.1145\/2382577.2382582","volume":"6","author":"R Chattopadhyay","year":"2012","unstructured":"Chattopadhyay, R., Sun, Q., Fan, W., Davidson, I., Panchanathan, S., & Ye, J. (2012). Multisource domain adaptation and its application to early detection of fatigue. ACM Transactions on Knowledge Discovery from Data, 6(4), 18:1\u201318:26. doi: 10.1145\/2382577.2382582 .","journal-title":"ACM Transactions on Knowledge Discovery from Data"},{"key":"5577_CR12","doi-asserted-by":"crossref","unstructured":"Chen, B., Lam, W., Tsang, I., Wong, T. L. (2009). Extracting discriminative concepts for domain adaptation in text mining. In Proceedings of the 15th ACM SIGKDD international conference on knowledge discovery and data mining, KDD \u201909 (pp. 179\u2013188).","DOI":"10.1145\/1557019.1557045"},{"issue":"12","key":"5577_CR13","doi-asserted-by":"publisher","first-page":"2240","DOI":"10.1109\/TNNLS.2014.2308325","volume":"25","author":"L Cheng","year":"2014","unstructured":"Cheng, L., & Pan, S. J. (2014). Semi-supervised domain adaptation on manifolds. IEEE Transactions on Neural Networks and Learning Systems, 25(12), 2240\u20132249. doi: 10.1109\/TNNLS.2014.2308325 .","journal-title":"IEEE Transactions on Neural Networks and Learning Systems"},{"issue":"6","key":"5577_CR14","doi-asserted-by":"crossref","first-page":"391","DOI":"10.1002\/(SICI)1097-4571(199009)41:6<391::AID-ASI1>3.0.CO;2-9","volume":"41","author":"S Deerwester","year":"1990","unstructured":"Deerwester, S., Dumais, S. T., Furnas, G. W., Landauer, T. K., & Harshman, R. (1990). Indexing by latent semantic analysis. Journal of the American Society for Information Science, 41(6), 391\u2013407.","journal-title":"Journal of the American Society for Information Science"},{"key":"5577_CR15","unstructured":"Dud\u00edk, M., Schapire, R. E., Phillips, S. J. (2005). Correcting sample selection bias in maximum entropy density estimation. In NIPS."},{"issue":"2","key":"5577_CR16","doi-asserted-by":"publisher","first-page":"303","DOI":"10.1137\/S0895479895290954","volume":"20","author":"A Edelman","year":"1999","unstructured":"Edelman, A., Arias, T. A., & Smith, S. T. (1999). The geometry of algorithms with orthogonality constraints. SIAM Journal on Matrix Analysis and Applications, 20(2), 303\u2013353. doi: 10.1137\/S0895479895290954 .","journal-title":"SIAM Journal on Matrix Analysis and Applications"},{"key":"5577_CR17","unstructured":"Gong, B., Grauman, K., Sha, F. (2013). Connecting the dots with landmarks: Discriminatively learning domain-invariant features for unsupervised domain adaptation. In Proceedings of the 30th international conference on machine learning, ICML (pp. 222\u2013230)."},{"key":"5577_CR18","unstructured":"Gong, B., Shi, Y., Sha, F., Grauman, K. (2012). Geodesic flow kernel for unsupervised domain adaptation. In CVPR, IEEE (pp. 2066\u20132073)."},{"key":"5577_CR19","doi-asserted-by":"publisher","unstructured":"Gopalan, R., Li, R., Chellappa, R. (2011). Domain adaptation for object recognition: An unsupervised approach. In Proceedings of the 2011 international conference on computer vision, ICCV \u201911 (pp. 999\u20131006). doi: 10.1109\/ICCV.2011.6126344 .","DOI":"10.1109\/ICCV.2011.6126344"},{"key":"5577_CR20","unstructured":"Gretton, A., Borgwardt, K. M., Rasch, M. J., Sch\u00f6lkopf, B., Smola, A. J. (2008). A kernel method for the two-sample problem. CoRR abs\/0805.2368."},{"key":"5577_CR21","first-page":"601","volume":"19","author":"J Huang","year":"2007","unstructured":"Huang, J., Smola, A. J., Gretton, A., Borgwardt, K. M., & Sch\u00f6lkopf, B. (2007). Correcting sample selection Bias by unlabeled data. Advances in Neural Information Processing Systems, 19, 601\u2013608.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"5577_CR22","first-page":"361","volume":"5","author":"DD Lewis","year":"2004","unstructured":"Lewis, D. D., Yang, Y., Rose, T. G., & Li, F. (2004). Rcv1: A new benchmark collection for text categorization research. The Journal of Machine Learning Research, 5, 361\u2013397.","journal-title":"The Journal of Machine Learning Research"},{"key":"5577_CR23","doi-asserted-by":"publisher","unstructured":"Long, M., Wang, J., Ding, G., Sun, J., Yu, P. S. (2013). Transfer feature learning with joint distribution adaptation. In 2013 IEEE International Conference on Computer Vision (ICCV) (pp. 2200\u20132207). doi: 10.1109\/ICCV.2013.274 .","DOI":"10.1109\/ICCV.2013.274"},{"key":"5577_CR24","doi-asserted-by":"publisher","unstructured":"McAuley, J., & Leskovec, J. (2013). Hidden factors and hidden topics: Understanding rating dimensions with review text. In Proceedings of the 7th ACM conference on recommender systems (pp. 165\u2013172). ACM, New York, NY, RecSys \u201913. doi: 10.1145\/2507157.2507163 .","DOI":"10.1145\/2507157.2507163"},{"key":"5577_CR25","first-page":"592","volume":"54","author":"F Mezzadri","year":"2007","unstructured":"Mezzadri, F. (2007). How to generate random matrices from the classical compact groups. Notices of the AMS, 54, 592\u2013604.","journal-title":"Notices of the AMS"},{"key":"5577_CR26","unstructured":"Muandet, K., Balduzzi, D., Sch\u00f6lkopf, B. (2013) . Domain generalization via invariant feature representation. CoRR abs\/1301.2115."},{"key":"5577_CR27","doi-asserted-by":"publisher","unstructured":"Ni, J., Qiu, Q., Chellappa, R. (2013). Subspace interpolation via dictionary learning for unsupervised domain adaptation. In Proceedings of the 2013 IEEE conference on computer vision and pattern recognition, CVPR \u201913 (pp. 692\u2013699). doi: 10.1109\/CVPR.2013.95 .","DOI":"10.1109\/CVPR.2013.95"},{"key":"5577_CR28","unstructured":"Pan, S. J., Kwok, J. T., Yang, Q. (2008). Transfer learning via dimensionality reduction. In Proceedings of the 23rd National Conference on Artificial Intelligence - Vol. 2 (pp. 677\u2013682). AAAI Press, AAAI\u201908. http:\/\/dl.acm.org\/citation.cfm?id=1620163.1620177 ."},{"key":"5577_CR29","unstructured":"Pan, S. J., Tsang, I. W., Kwok, J. T., Yang, Q. (2009). Domain adaptation via transfer component analysis. In Proceedings of the 21st international joint conference on artifical intelligence, IJCAI\u201909 (pp. 1187\u20131192)."},{"issue":"2","key":"5577_CR30","doi-asserted-by":"publisher","first-page":"199","DOI":"10.1109\/TNN.2010.2091281","volume":"22","author":"SJ Pan","year":"2011","unstructured":"Pan, S. J., Tsang, I. W., Kwok, J. T., & Yang, Q. (2011). Domain adaptation via transfer component analysis. IEEE Transactions on Neural Networks, 22(2), 199\u2013210. doi: 10.1109\/TNN.2010.2091281 .","journal-title":"IEEE Transactions on Neural Networks"},{"key":"5577_CR31","first-page":"1104","volume":"12","author":"M Shao","year":"2012","unstructured":"Shao, M., Castillo, C., Gu, Z., & Fu, Y. (2012). Low-rank transfer subspace learning. IEEE International Conference on Data Mining, 12, 1104\u20131109.","journal-title":"IEEE International Conference on Data Mining"},{"issue":"7","key":"5577_CR32","doi-asserted-by":"crossref","first-page":"929","DOI":"10.1109\/TKDE.2009.126","volume":"22","author":"S Si","year":"2010","unstructured":"Si, S., Tao, D., & Geng, B. (2010). Bregman divergence-based regularization for transfer subspace learning. IEEE Transactions on Knowledge and Data Engineering, 22(7), 929\u2013942.","journal-title":"IEEE Transactions on Knowledge and Data Engineering"},{"key":"5577_CR33","unstructured":"Sugiyama, M., Nakajima, S., Kashima, H., von B\u00fcnau, P., Kawanabe, M. (2007). Direct importance estimation with model selection and its application to covariate shift adaptation. In NIPS."},{"key":"5577_CR34","unstructured":"Sugiyama, M., Nakajima, S., Kashima, H., von B\u00fcnau, P., Kawanabe, M. (2008). Direct importance estimation with model selectionand its application to covariate shift adaptation. In Advances in neural information processing systems 20."},{"key":"5577_CR35","first-page":"2579","volume":"9","author":"L Maaten van der","year":"2008","unstructured":"van der Maaten, L., & Hinton, G. E. (2008). Visualizing high-dimensional data using t-sne. Journal of Machine Learning Research, 9, 2579\u20132605.","journal-title":"Journal of Machine Learning Research"},{"issue":"1\u20132","key":"5577_CR36","doi-asserted-by":"crossref","first-page":"397","DOI":"10.1007\/s10107-012-0584-1","volume":"142","author":"Z Wen","year":"2013","unstructured":"Wen, Z., & Yin, W. (2013). A feasible method for optimization with orthogonality constraints. Math Program, 142(1\u20132), 397\u2013434.","journal-title":"Math Program"},{"key":"5577_CR37","unstructured":"Zhang, K., Zheng, V., Wang, Q., Kwok, J., Yang, Q., Marsic, I. (2013). Covariate shift in Hilbert space: A solution via sorrogate kernels. In Proceedings of the 30th International Conference on Machine Learning (ICML-13), vol\u00a028 (pp. 388\u2013395)."}],"container-title":["Machine Learning"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10994-016-5577-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s10994-016-5577-5\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10994-016-5577-5","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2017,6,24]],"date-time":"2017-06-24T15:41:19Z","timestamp":1498318879000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s10994-016-5577-5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,8,1]]},"references-count":37,"journal-issue":{"issue":"2-3","published-print":{"date-parts":[[2016,9]]}},"alternative-id":["5577"],"URL":"https:\/\/doi.org\/10.1007\/s10994-016-5577-5","relation":{},"ISSN":["0885-6125","1573-0565"],"issn-type":[{"type":"print","value":"0885-6125"},{"type":"electronic","value":"1573-0565"}],"subject":[],"published":{"date-parts":[[2016,8,1]]}}}