{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,30]],"date-time":"2026-04-30T03:39:17Z","timestamp":1777520357442,"version":"3.51.4"},"reference-count":24,"publisher":"Institute of Electronics, Information and Communications Engineers (IEICE)","issue":"10","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEICE Trans. Inf. & Syst."],"published-print":{"date-parts":[[2017]]},"DOI":"10.1587\/transinf.2017edp7184","type":"journal-article","created":{"date-parts":[[2017,9,30]],"date-time":"2017-09-30T22:24:47Z","timestamp":1506810287000},"page":"2597-2604","source":"Crossref","is-referenced-by-count":9,"title":["READER: Robust Semi-Supervised Multi-Label Dimension Reduction"],"prefix":"10.1587","volume":"E100.D","author":[{"given":"Lu","family":"SUN","sequence":"first","affiliation":[{"name":"Graduate School of Information Science and Technology, Hokkaido University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mineichi","family":"KUDO","sequence":"additional","affiliation":[{"name":"Graduate School of Information Science and Technology, Hokkaido University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Keigo","family":"KIMURA","sequence":"additional","affiliation":[{"name":"Graduate School of Information Science and Technology, Hokkaido University"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"532","reference":[{"key":"1","doi-asserted-by":"crossref","unstructured":"[1] K. Yu, S. Yu, and V. Tresp, \u201cMulti-label informed latent semantic indexing,\u201d Proceedings of the 28th ACM SIGIR, SIGIR '05, pp.258-265, 2005. 10.1145\/1076034.1076080","DOI":"10.1145\/1076034.1076080"},{"key":"2","doi-asserted-by":"publisher","unstructured":"[2] M.R. Boutell, J. Luo, X. Shen, and C.M. Brown, \u201cLearning multi-label scene classification,\u201d Patt. Recog., vol.37, no.9, pp.1757-1771, 2004. 10.1016\/j.patcog.2004.03.009","DOI":"10.1016\/j.patcog.2004.03.009"},{"key":"3","doi-asserted-by":"publisher","unstructured":"[3] M.-L. Zhang and Z.-H. Zhou, \u201cMl-knn: A lazy learning approach to multi-label learning,\u201d Patt. Recog., vol.40, no.7, pp.2038-2048, 2007. 10.1016\/j.patcog.2006.12.019","DOI":"10.1016\/j.patcog.2006.12.019"},{"key":"4","doi-asserted-by":"crossref","unstructured":"[4] T. Hastie, R. Tibshirani, and J. Friedman, The elements of statistical learning: data mining, inference and prediction, 2 ed., Springer, 2009.","DOI":"10.1007\/978-0-387-84858-7"},{"key":"5","unstructured":"[5] J. Liu, S. Ji, and J. Ye, \u201cMulti-task feature learning via efficient l2, 1-norm minimization,\u201d Proceedings of the 25th UAI, pp.339-348, 2009."},{"key":"6","unstructured":"[6] F. Nie, H. Huang, X. Cai, and C.H. Ding, \u201cEfficient and robust feature selection via joint l2,1-norms minimization,\u201d in Advances in NIPS 23, pp.1813-1821, 2010."},{"key":"7","doi-asserted-by":"publisher","unstructured":"[7] Z. Ma, F. Nie, Y. Yang, J.R.R. Uijlings, N. Sebe, and A.G. Hauptmann, \u201cDiscriminating joint feature analysis for multimedia data understanding,\u201d IEEE Trans. Multimedia, vol.14, no.6, pp.1662-1672, Dec. 2012. 10.1109\/tmm.2012.2199293","DOI":"10.1109\/TMM.2012.2199293"},{"key":"8","unstructured":"[8] X. Chang, F. Nie, Y. Yang, and H. Huang, \u201cA convex formulation for semi-supervised multi-label feature selection,\u201d in Proceedings of the 28th AAAI, pp.1171-1177, 2014."},{"key":"9","doi-asserted-by":"publisher","unstructured":"[9] Y. Zhang and Z.-H. Zhou, \u201cMultilabel dimensionality reduction via dependence maximization,\u201d ACM Trans. KDD, vol.4, no.3, pp.14:1-14:21, Oct. 2010. 10.1145\/1839490.1839495","DOI":"10.1145\/1839490.1839495"},{"key":"10","doi-asserted-by":"publisher","unstructured":"[10] L. Sun, S. Ji, and J. Ye, \u201cCanonical correlation analysis for multilabel classification: A least-squares formulation, extensions, and analysis,\u201d IEEE Trans. PAMI, vol.33, no.1, pp.194-200, 2011. 10.1109\/tpami.2010.160","DOI":"10.1109\/TPAMI.2010.160"},{"key":"11","doi-asserted-by":"crossref","unstructured":"[11] H. Wang, C. Ding, and H. Huang, \u201cMulti-label linear discriminant analysis,\u201d in Proceedings of the 11th ECCV, vol.6316, pp.126-139, 2010. 10.1007\/978-3-642-15567-3_10","DOI":"10.1007\/978-3-642-15567-3_10"},{"key":"12","unstructured":"[12] A. Kimura, M. Sugiyama, T. Nakano, H. Kameoka, H. Sakano, E. Maeda, and K. Ishiguro, \u201cSemicca: Efficient semi-supervised learning of canonical correlations,\u201d Information and Media Technologies, vol.8, no.2, pp.311-318, 2013."},{"key":"13","doi-asserted-by":"crossref","unstructured":"[13] C. Kamada, A. Kanezaki, and T. Harada, \u201cProbabilistic semi-canonical correlation analysis,\u201d Proceedings of the 23rd ACM international conference on Multimedia, pp.1131-1134, ACM, 2015. 10.1145\/2733373.2806299","DOI":"10.1145\/2733373.2806299"},{"key":"14","doi-asserted-by":"crossref","unstructured":"[14] J. Huang, G. Li, Q. Huang, and X. Wu, \u201cLearning label specific features for multi-label classification,\u201d 2015 IEEE ICDM, pp.181-190, 2015. 10.1109\/icdm.2015.67","DOI":"10.1109\/ICDM.2015.67"},{"key":"15","doi-asserted-by":"crossref","unstructured":"[15] L. Sun, M. Kudo, and K. Kimura, \u201cMulti-label classification with meta-label-specific features,\u201d Proceedings of the 23rd ICPR, pp.1612-1617, 2016. 10.1109\/icpr.2016.7899867","DOI":"10.1109\/ICPR.2016.7899867"},{"key":"16","doi-asserted-by":"publisher","unstructured":"[16] Z. Ma, F. Nie, Y. Yang, J.R.R. Uijlings, and N. Sebe, \u201cWeb image annotation via subspace-sparsity collaborated feature selection,\u201d IEEE Trans. Multimedia, vol.14, no.4, pp.1021-1030, Aug. 2012. 10.1109\/tmm.2012.2187179","DOI":"10.1109\/TMM.2012.2187179"},{"key":"17","unstructured":"[17] L. Jian, J. Li, K. Shu, and H. Liu, \u201cMulti-label informed feature selection,\u201d Proceedings of the 25th IJCAI, pp.1627-1633, 2016."},{"key":"18","unstructured":"[18] K. Bhatia, H. Jain, P. Kar, M. Varma, and P. Jain, \u201cSparse local embeddings for extreme multi-label classification,\u201d in Advances in NIPS 28, pp.730-738, 2015."},{"key":"19","unstructured":"[19] Y. Chen and H. Lin, \u201cFeature-aware label space dimension reduction for multi-label classification,\u201d in Advances in NIPS 25, pp.1529-1537, 2012."},{"key":"20","unstructured":"[20] G. Tsoumakas, E. Spyromitros-Xioufis, J. Vilcek, and I. Vlahavas, \u201cMulan: A java library for multi-label learning,\u201d Journal of Machine Learning Research, vol.12, pp.2411-2414, 2011."},{"key":"21","doi-asserted-by":"crossref","unstructured":"[21] M.J. Huiskes and M.S. Lew, \u201cThe mir flickr retrieval evaluation,\u201d Proceedings of the 1st ACM international conference on Multimedia information retrieval, pp.39-43, ACM, 2008. 10.1145\/1460096.1460104","DOI":"10.1145\/1460096.1460104"},{"key":"22","unstructured":"[22] R. Duda, P. Hart, and D. Stork, Pattern Classification, 2 ed., John Wiley & Sons, New York, 2001."},{"key":"23","doi-asserted-by":"publisher","unstructured":"[23] J. Zhao, K. Lu, and X. He, \u201cLocality sensitive semi-supervised feature selection,\u201d Neurocomputing, vol.71, no.10-12, pp.1842-1849, 2008. 10.1016\/j.neucom.2007.06.014","DOI":"10.1016\/j.neucom.2007.06.014"},{"key":"24","unstructured":"[24] R.E. Fan, K.W. Chang, C.J. Hsieh, X.R. Wang, and C.J. Lin, \u201cLIBLINEAR: A library for large linear classification,\u201d Journal of Machine Learning Research, vol.9, pp.1871-1874, 2008."}],"container-title":["IEICE Transactions on Information and Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.jstage.jst.go.jp\/article\/transinf\/E100.D\/10\/E100.D_2017EDP7184\/_pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,10,4]],"date-time":"2019-10-04T04:34:40Z","timestamp":1570163680000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.jstage.jst.go.jp\/article\/transinf\/E100.D\/10\/E100.D_2017EDP7184\/_article"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017]]},"references-count":24,"journal-issue":{"issue":"10","published-print":{"date-parts":[[2017]]}},"URL":"https:\/\/doi.org\/10.1587\/transinf.2017edp7184","relation":{},"ISSN":["0916-8532","1745-1361"],"issn-type":[{"value":"0916-8532","type":"print"},{"value":"1745-1361","type":"electronic"}],"subject":[],"published":{"date-parts":[[2017]]}}}