{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T18:10:16Z","timestamp":1777486216266,"version":"3.51.4"},"publisher-location":"Cham","reference-count":31,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030110178","type":"print"},{"value":"9783030110185","type":"electronic"}],"license":[{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019]]},"DOI":"10.1007\/978-3-030-11018-5_47","type":"book-chapter","created":{"date-parts":[[2019,1,24]],"date-time":"2019-01-24T05:50:50Z","timestamp":1548309050000},"page":"593-608","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":56,"title":["Incomplete Multi-view Clustering via Graph Regularized Matrix Factorization"],"prefix":"10.1007","author":[{"given":"Jie","family":"Wen","sequence":"first","affiliation":[]},{"given":"Zheng","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Yong","family":"Xu","sequence":"additional","affiliation":[]},{"given":"Zuofeng","family":"Zhong","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2019,1,23]]},"reference":[{"key":"47_CR1","doi-asserted-by":"crossref","unstructured":"Blum, A., Mitchell, T.: Combining labeled and unlabeled data with co-training. In: COLT, pp. 92\u2013100. ACM (1998)","DOI":"10.1145\/279943.279962"},{"key":"47_CR2","unstructured":"Cai, X., Nie, F., Huang, H.: Multi-view k-means clustering on big data. In: IJCAI, pp. 2598\u20132604 (2013)"},{"key":"47_CR3","doi-asserted-by":"publisher","first-page":"264","DOI":"10.1016\/j.neucom.2016.08.048","volume":"218","author":"L Fei","year":"2016","unstructured":"Fei, L., Xu, Y., Zhang, B., Fang, X., Wen, J.: Low-rank representation integrated with principal line distance for contactless palmprint recognition. Neurocomputing 218, 264\u2013275 (2016)","journal-title":"Neurocomputing"},{"issue":"1","key":"47_CR4","doi-asserted-by":"publisher","first-page":"59","DOI":"10.1016\/j.cviu.2005.09.012","volume":"106","author":"L Fei-Fei","year":"2007","unstructured":"Fei-Fei, L., Fergus, R., Perona, P.: Learning generative visual models from few training examples: an incremental bayesian approach tested on 101 object categories. Comput. Vis. Image Underst. 106(1), 59\u201370 (2007)","journal-title":"Comput. Vis. Image Underst."},{"key":"47_CR5","series-title":"IFIP Advances in Information and Communication Technology","doi-asserted-by":"publisher","first-page":"245","DOI":"10.1007\/978-3-319-48390-0_25","volume-title":"Intelligent Information Processing VIII","author":"H Gao","year":"2016","unstructured":"Gao, H., Peng, Y., Jian, S.: Incomplete multi-view clustering. In: Shi, Z., Vadera, S., Li, G. (eds.) IIP 2016. IAICT, vol. 486, pp. 245\u2013255. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-48390-0_25"},{"key":"47_CR6","doi-asserted-by":"crossref","unstructured":"Guo, Y.: Convex subspace representation learning from multi-view data. In: AAAI, vol. 1, pp. 387\u2013393 (2013)","DOI":"10.1609\/aaai.v27i1.8565"},{"key":"47_CR7","unstructured":"Huang, D., Sun, J., Wang, Y.: The buaa-visnir face database instructions. Technical report IRIP-TR-12-FR-001, School of Computational Science and Engineering, Beihang University, Beijing, China (2012)"},{"key":"47_CR8","unstructured":"Kumar, A., Rai, P., Daume, H.: Co-regularized multi-view spectral clustering. In: NIPS, pp. 1413\u20131421 (2011)"},{"key":"47_CR9","unstructured":"Li, M., Xue, X.B., Zhou, Z.H.: Exploiting multi-modal interactions: a unified framework. In: IJCAI, pp. 1120\u20131125 (2009)"},{"key":"47_CR10","doi-asserted-by":"crossref","unstructured":"Li, Y., Nie, F., Huang, H., Huang, J.: Large-scale multi-view spectral clustering via bipartite graph. In: AAAI, pp. 2750\u20132756 (2015)","DOI":"10.1609\/aaai.v29i1.9598"},{"issue":"1","key":"47_CR11","doi-asserted-by":"publisher","first-page":"171","DOI":"10.1109\/TPAMI.2012.88","volume":"35","author":"G Liu","year":"2013","unstructured":"Liu, G., Lin, Z., Yan, S., Sun, J., Yu, Y., Ma, Y.: Robust recovery of subspace structures by low-rank representation. IEEE TPAMI 35(1), 171\u2013184 (2013)","journal-title":"IEEE TPAMI"},{"key":"47_CR12","unstructured":"Ngiam, J., Khosla, A., Kim, M., Nam, J., Lee, H., Ng, A.Y.: Multimodal deep learning. In: ICML, pp. 689\u2013696 (2011)"},{"key":"47_CR13","doi-asserted-by":"crossref","unstructured":"Qian, B., Shen, X., Gu, Y., Tang, Z., Ding, Y.: Double constrained NMF for partial multi-view clustering. In: DICTA, pp. 1\u20137. IEEE (2016)","DOI":"10.1109\/DICTA.2016.7797034"},{"key":"47_CR14","doi-asserted-by":"crossref","unstructured":"Qin, J., et al.: Binary coding for partial action analysis with limited observation ratios. In: CVPR, pp. 146\u2013155 (2017)","DOI":"10.1109\/CVPR.2017.712"},{"key":"47_CR15","doi-asserted-by":"crossref","unstructured":"Qin, J., et al.: Zero-shot action recognition with error-correcting output codes. In: CVPR, pp. 2833\u20132842 (2017)","DOI":"10.1109\/CVPR.2017.117"},{"key":"47_CR16","doi-asserted-by":"crossref","unstructured":"Rai, N., Negi, S., Chaudhury, S., Deshmukh, O.: Partial multi-view clustering using graph regularized NMF. In: ICPR, pp. 2192\u20132197. IEEE (2016)","DOI":"10.1109\/ICPR.2016.7899961"},{"key":"47_CR17","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"318","DOI":"10.1007\/978-3-319-23528-8_20","volume-title":"Machine Learning and Knowledge Discovery in Databases","author":"W Shao","year":"2015","unstructured":"Shao, W., He, L., Yu, P.S.: Multiple incomplete views clustering via weighted nonnegative matrix factorization with $$L_{2,1}$$ regularization. In: Appice, A., Rodrigues, P.P., Santos Costa, V., Soares, C., Gama, J., Jorge, A. (eds.) ECML PKDD 2015. LNCS (LNAI), vol. 9284, pp. 318\u2013334. Springer, Cham (2015). https:\/\/doi.org\/10.1007\/978-3-319-23528-8_20"},{"key":"47_CR18","unstructured":"Trivedi, A., Rai, P., Daum\u00e9 III, H., DuVall, S.L.: Multiview clustering with incomplete views. In: NIPSW, pp. 1\u20137 (2010)"},{"key":"47_CR19","doi-asserted-by":"publisher","unstructured":"Wen, J., et al.: Robust sparse linear discriminant analysis. In: IEEE TCSVT (2018). https:\/\/doi.org\/10.1109\/TCSVT.2018.2799214","DOI":"10.1109\/TCSVT.2018.2799214"},{"key":"47_CR20","doi-asserted-by":"publisher","first-page":"83","DOI":"10.1016\/j.neunet.2018.08.007","volume":"108","author":"J Wen","year":"2018","unstructured":"Wen, J., Fang, X., Xu, Y., Tian, C., Fei, L.: Low-rank representation with adaptive graph regularization. Neural Netw. 108, 83\u201396 (2018)","journal-title":"Neural Netw."},{"key":"47_CR21","doi-asserted-by":"publisher","unstructured":"Wen, J., Han, N., Fang, X., Fei, L., Yan, K., Zhan, S.: Low-rank preserving projection via graph regularized reconstruction. In: IEEE TCYB, vol. 99, pp. 1\u201313 (2018). https:\/\/doi.org\/10.1109\/TCYB.2018.2799862","DOI":"10.1109\/TCYB.2018.2799862"},{"key":"47_CR22","doi-asserted-by":"publisher","first-page":"662","DOI":"10.1016\/j.patcog.2017.09.043","volume":"76","author":"Y Zhang","year":"2018","unstructured":"Zhang, Y., Zhang, Z., Qin, J., Zhang, L., Li, B., Li, F.: Semi-supervised local multi-manifold isomap by linear embedding for feature extraction. Pattern Recogn. 76, 662\u2013678 (2018)","journal-title":"Pattern Recogn."},{"issue":"10","key":"47_CR23","first-page":"2192","volume":"25","author":"Z Zhang","year":"2013","unstructured":"Zhang, Z., Zhao, M., Chow, T.W.: Binary-and multi-class group sparse canonical correlation analysis for feature extraction and classification. IEEE TKDE 25(10), 2192\u20132205 (2013)","journal-title":"IEEE TKDE"},{"issue":"3","key":"47_CR24","first-page":"1466","volume":"26","author":"Z Zhang","year":"2017","unstructured":"Zhang, Z., Lai, Z., Xu, Y., Shao, L., Wu, J., Xie, G.S.: Discriminative elastic-net regularized linear regression. IEEE TIP 26(3), 1466\u20131481 (2017)","journal-title":"IEEE TIP"},{"key":"47_CR25","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"731","DOI":"10.1007\/978-3-030-01258-8_44","volume-title":"Computer Vision \u2013 ECCV 2018","author":"Z Zhang","year":"2018","unstructured":"Zhang, Z., et al.: Highly-economized multi-view binary compression for scalable image clustering. In: Ferrari, V., Hebert, M., Sminchisescu, C., Weiss, Y. (eds.) ECCV 2018, Part XII. LNCS, vol. 11216, pp. 731\u2013748. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-030-01258-8_44"},{"issue":"10","key":"47_CR26","doi-asserted-by":"publisher","first-page":"4645","DOI":"10.1109\/TNNLS.2017.2772264","volume":"29","author":"Zheng Zhang","year":"2018","unstructured":"Zhang, Z., Shao, L., Xu, Y., Liu, L., Yang, J.: Marginal representation learning with graph structure self-adaptation. IEEE TNNLS (2017). https:\/\/doi.org\/10.1109\/TNNLS.2017.2772264","journal-title":"IEEE Transactions on Neural Networks and Learning Systems"},{"issue":"7","key":"47_CR27","first-page":"3111","volume":"29","author":"Z Zhang","year":"2018","unstructured":"Zhang, Z., Xu, Y., Shao, L., Yang, J.: Discriminative block-diagonal representation learning for image recognition. IEEE TNNLS 29(7), 3111\u20133125 (2018)","journal-title":"IEEE TNNLS"},{"key":"47_CR28","unstructured":"Zhao, H., Liu, H., Fu, Y.: Incomplete multi-modal visual data grouping. In: IJCAI, pp. 2392\u20132398 (2016)"},{"key":"47_CR29","doi-asserted-by":"publisher","first-page":"43","DOI":"10.1016\/j.inffus.2017.02.007","volume":"38","author":"J Zhao","year":"2017","unstructured":"Zhao, J., Xie, X., Xu, X., Sun, S.: Multi-view learning overview: recent progress and new challenges. Inf. Fusion 38, 43\u201354 (2017)","journal-title":"Inf. Fusion"},{"key":"47_CR30","unstructured":"Zhi, S.Y., Zhou, H.: Partial multi-view clustering. In: AAAI, pp. 1968\u20131974 (2014)"},{"issue":"2","key":"47_CR31","doi-asserted-by":"publisher","first-page":"265","DOI":"10.1198\/106186006X113430","volume":"15","author":"H Zou","year":"2006","unstructured":"Zou, H., Hastie, T., Tibshirani, R.: Sparse principal component analysis. J. Comput. Graph. Stat. 15(2), 265\u2013286 (2006)","journal-title":"J. Comput. Graph. Stat."}],"container-title":["Lecture Notes in Computer Science","Computer Vision \u2013 ECCV 2018 Workshops"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-11018-5_47","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,1,22]],"date-time":"2023-01-22T01:25:39Z","timestamp":1674350739000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-11018-5_47"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"ISBN":["9783030110178","9783030110185"],"references-count":31,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-11018-5_47","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019]]},"assertion":[{"value":"23 January 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ECCV","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"European Conference on Computer Vision","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Munich","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Germany","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2018","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8 September 2018","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14 September 2018","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"eccv2018","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/eccv2018.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"This content has been made available to all.","name":"free","label":"Free to read"}]}}