{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,16]],"date-time":"2025-10-16T10:09:49Z","timestamp":1760609389208,"version":"3.37.3"},"reference-count":48,"publisher":"Springer Science and Business Media LLC","issue":"10","license":[{"start":{"date-parts":[[2021,8,6]],"date-time":"2021-08-06T00:00:00Z","timestamp":1628208000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,8,6]],"date-time":"2021-08-06T00:00:00Z","timestamp":1628208000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Int. J. Mach. Learn. &amp; Cyber."],"published-print":{"date-parts":[[2021,10]]},"DOI":"10.1007\/s13042-021-01370-0","type":"journal-article","created":{"date-parts":[[2021,8,6]],"date-time":"2021-08-06T12:02:36Z","timestamp":1628251356000},"page":"2843-2857","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Diversity-promoting multi-view graph learning for semi-supervised classification"],"prefix":"10.1007","volume":"12","author":[{"given":"Shanhua","family":"Zhan","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2342-4434","authenticated-orcid":false,"given":"Weijun","family":"Sun","sequence":"additional","affiliation":[]},{"given":"Cuifeng","family":"Du","sequence":"additional","affiliation":[]},{"given":"Weifang","family":"Zhong","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2021,8,6]]},"reference":[{"key":"1370_CR1","doi-asserted-by":"crossref","unstructured":"Bickel S, Scheffer T (2004) Multi-view clustering. In: Proceedings of the IEEE international conference on data mining, pp 19\u201326","DOI":"10.1109\/ICDM.2004.10095"},{"key":"1370_CR2","unstructured":"Xie P, Zhu J, Xing EP (2016) Diversity-promoting bayesian learning of latent variable models. In: International Conference on International Conference on Machine Learning, pp 59\u201368"},{"key":"1370_CR3","doi-asserted-by":"crossref","unstructured":"Cao X, Zhang C, Fu H, Liu S, Zhang H (2015) Diversity-induced multi-view subspace clustering. In; IEEE Conference on computer vision and pattern recognition, pp 7\u201312","DOI":"10.1109\/CVPR.2015.7298657"},{"issue":"12","key":"1370_CR4","doi-asserted-by":"publisher","first-page":"2531","DOI":"10.1109\/TPAMI.2015.2417578","volume":"37","author":"C Xu","year":"2015","unstructured":"Xu C, Tao D, Xu C (2015) Multi-view intact space learning. IEEE Trans Pattern Anal Mach Intell 37(12):2531\u20132544","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"12","key":"1370_CR5","doi-asserted-by":"publisher","first-page":"5552","DOI":"10.1109\/TIP.2016.2609820","volume":"25","author":"C Hou","year":"2016","unstructured":"Hou C, Tsai Y, Yeh Y, Wang Y (2016) Unsupervised domain adaptation with label and structural consistency. IEEE Trans Image Process 25(12):5552\u20135562","journal-title":"IEEE Trans Image Process"},{"issue":"10","key":"1370_CR6","doi-asserted-by":"publisher","first-page":"4959","DOI":"10.1109\/TIP.2016.2598679","volume":"25","author":"L Zhang","year":"2016","unstructured":"Zhang L, Zhang D (2016) Robust visual knowledge transfer via extreme learning machine based domain adaptation. IEEE Trans Image Process 25(10):4959\u20134973","journal-title":"IEEE Trans Image Process"},{"issue":"5","key":"1370_CR7","doi-asserted-by":"publisher","first-page":"1019","DOI":"10.1109\/TNNLS.2014.2330900","volume":"26","author":"L Shao","year":"2015","unstructured":"Shao L, Zhu F, Li X (2015) Transfer learning for visual categorization: a survey. IEEE Trans Neural Netw Learn Syst 26(5):1019\u20131034","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"issue":"2","key":"1370_CR8","doi-asserted-by":"publisher","first-page":"310","DOI":"10.1109\/TNNLS.2016.2618765","volume":"29","author":"Z Ding","year":"2016","unstructured":"Ding Z, Shao M, Fu Y (2016) Incomplete multisource transfer learning. IEEE Trans Neural Netw Learn Syst 29(2):310\u2013323","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"issue":"2","key":"1370_CR9","doi-asserted-by":"publisher","first-page":"850","DOI":"10.1109\/TIP.2015.2510498","volume":"25","author":"Y Xu","year":"2016","unstructured":"Xu Y, Fang X, Wu J, Li X, Zhang D (2016) Discriminative transfer subspace learning via low-rank and sparse representation. IEEE Trans Image Process 25(2):850\u2013863","journal-title":"IEEE Trans Image Process"},{"key":"1370_CR10","doi-asserted-by":"crossref","unstructured":"Szafranski M, Grandvalet Y, Rakotomamonjy A (2008) Composite kernel learning. In: Proceedings of the 25th international conference on machine learning, pp 1040\u20131047","DOI":"10.1145\/1390156.1390287"},{"issue":"1","key":"1370_CR11","doi-asserted-by":"publisher","first-page":"73","DOI":"10.1007\/s10994-009-5150-6","volume":"79","author":"M Szafranski","year":"2010","unstructured":"Szafranski M, Grandvalet Y, Rakotomamonjy A (2010) Composite kernel learning. Mach Learn 79(1):73\u2013103","journal-title":"Mach Learn"},{"key":"1370_CR12","doi-asserted-by":"crossref","unstructured":"Varma M, Babu BR (2009) More generality in efficient multiple kernel learning. In: Proceedings of the 26th annual international conference on machine learning, pp 1065\u20131072","DOI":"10.1145\/1553374.1553510"},{"issue":"2","key":"1370_CR13","doi-asserted-by":"publisher","first-page":"348","DOI":"10.1109\/TPAMI.2007.70786","volume":"30","author":"Z Wang","year":"2008","unstructured":"Wang Z, Chen S, Sun T (2008) Multik-MHKS: a novel multiple kernel learning algorithm. IEEE Trans Pattern Anal Mach Intell 30(2):348\u2013353","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"1370_CR14","unstructured":"Settles B (2009) Active learning literature survey. Computer Sciences Technical Report 1648. University of Wisconsin, Madison"},{"key":"1370_CR15","doi-asserted-by":"crossref","unstructured":"Seung HS, Opper M, Sompolinsky H (1992) Query by committee. In: Proceedings of the fifth annual workshop on Computational learning theory, pp 287\u2013294","DOI":"10.1145\/130385.130417"},{"issue":"7","key":"1370_CR16","doi-asserted-by":"publisher","first-page":"1340","DOI":"10.1109\/TPAMI.2013.180","volume":"36","author":"D Niu","year":"2014","unstructured":"Niu D, Dy JG, Jordan MI (2014) Iterative discovery of multiple alternative clustering views. IEEE Trans Pattern Anal Mach Intell 36(7):1340-1353.","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"1370_CR17","unstructured":"Chen N, Zhu J, Xing E (2010) Predictive subspace learning for multi-view data: a large margin approach. In: NIPS, pp 361\u2013369"},{"issue":"1","key":"1370_CR18","doi-asserted-by":"publisher","first-page":"188","DOI":"10.1109\/TPAMI.2015.2435740","volume":"38","author":"M Kan","year":"2016","unstructured":"Kan M, Shan S, Zhang H, Lao S, Chen X (2016) Multi-View discriminant analysis. IEEE Trans Pattern Anal Mach Intell 38(1):188\u2013194","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"7","key":"1370_CR19","doi-asserted-by":"publisher","first-page":"1921","DOI":"10.1109\/TIP.2010.2044958","volume":"19","author":"F Nie","year":"2010","unstructured":"Nie F, Xu D, Tsang IW, Zhang C (2010) Flexible manifold embedding: a framework for semi-supervised and unsupervised dimension reduction. IEEE Trans Image Process 19(7):1921\u20131932","journal-title":"IEEE Trans Image Process"},{"key":"1370_CR20","unstructured":"Zhu X, Ghahramani Z, Lafferty J (2003) Semi-supervised learning using Gaussian fields and harmonic functions. In: Proc. ICML, pp 912\u2013919"},{"key":"1370_CR21","first-page":"2399","volume":"7","author":"M Belkin","year":"2006","unstructured":"Belkin M, Niyogi P, Sindhwani V (2006) Manifold regularization: a geometric framework for learning from labeled and unlabeled examples. J Mach Learn Res 7:2399\u20132434","journal-title":"J Mach Learn Res"},{"key":"1370_CR22","doi-asserted-by":"crossref","unstructured":"Nie F, Cai G, Li X (2017) Multi-view clustering and semi-supervised classification with adaptive neighbours. In: The 31st AAAI Conference on Artificial Intelligence (AAAI). San Francisco,\u00a0 pp. 2408\u20132414","DOI":"10.1609\/aaai.v31i1.10909"},{"key":"1370_CR23","first-page":"1977","volume":"2011","author":"X Cai","year":"2011","unstructured":"Cai X, Nie FP, Huang H, Kamangar F (2011) Heterogeneous image feature integration via multi-modal spectral clustering. IEEE Conf Comput Vision Pattern Recogn 2011:1977\u20131984","journal-title":"IEEE Conf Comput Vision Pattern Recogn"},{"key":"1370_CR24","unstructured":"Kumar A, Rai P, Daume Hal (2011) Co-regularized multi-view spectral clustering. In: Advances in neural information processing systems, pp 1413\u20131421"},{"issue":"11","key":"1370_CR25","doi-asserted-by":"publisher","first-page":"4636","DOI":"10.1109\/TIP.2012.2207395","volume":"21","author":"J Yu","year":"2012","unstructured":"Yu J, Wang M, Tao DC (2012) Semisupervised multiview distance metric learning for cartoon synthesis. IEEE Trans Image Process 21(11):4636\u20134648","journal-title":"IEEE Trans Image Process"},{"issue":"4","key":"1370_CR26","doi-asserted-by":"publisher","first-page":"1279","DOI":"10.1109\/TCYB.2018.2799862","volume":"49","author":"J Wen","year":"2019","unstructured":"Wen J, Han N, Fang X, Fei L, Yan K, Zhan S (2019) Low-rank preserving projection via graph regularized reconstruction. IEEE Trans Cybern 49(4):1279\u20131291","journal-title":"IEEE Trans Cybern"},{"issue":"2","key":"1370_CR27","doi-asserted-by":"publisher","first-page":"390","DOI":"10.1109\/TCSVT.2018.2799214","volume":"29","author":"J Wen","year":"2019","unstructured":"Wen J, Fang X, Cui J, Fei L et al (2019) Robust sparse linear discriminant analysis. IEEE Trans Circuits Syst Video Technol 29(2):390\u2013403","journal-title":"IEEE Trans Circuits Syst Video Technol"},{"key":"1370_CR28","doi-asserted-by":"publisher","first-page":"36","DOI":"10.1016\/j.neunet.2018.02.002","volume":"102","author":"J Wen","year":"2018","unstructured":"Wen J, Xu Y, Li Z et al (2018) Inter-class sparsity based discriminative least square regression. Neural Netw 102:36\u201347","journal-title":"Neural Netw"},{"issue":"6","key":"1370_CR29","doi-asserted-by":"publisher","first-page":"1147","DOI":"10.1109\/TPAMI.2010.183","volume":"33","author":"YY Lin","year":"2011","unstructured":"Lin YY, Liu TL, Huh CS (2011) Multiple kernel learning for dimenisonality reduction. IEEE Trans Patten Anal Mach Intell 33(6):1147\u20131160","journal-title":"IEEE Trans Patten Anal Mach Intell"},{"key":"1370_CR30","first-page":"2211","volume":"12","author":"M Gonen","year":"2011","unstructured":"Gonen M, Alpaydin E (2011) Multiple kernel learning algorithms. J Mach Learn Res 12:2211\u20132268","journal-title":"J Mach Learn Res"},{"key":"1370_CR31","doi-asserted-by":"crossref","unstructured":"Tang W, Lu Z, Dhillon IS (2009) Clustering with multiple graphs. In: Proceedings of the 9th IEEE international conference on data mining, pp. 1016\u20131021","DOI":"10.1109\/ICDM.2009.125"},{"issue":"12","key":"1370_CR32","doi-asserted-by":"publisher","first-page":"1999","DOI":"10.1109\/TNNLS.2013.2271327","volume":"24","author":"M Karasuyama","year":"2013","unstructured":"Karasuyama M, Mamitsuka H (2013) Multiple graph label propagation by sparse integration. IEEE Trans Neural Netw Learn Syst 24(12):1999\u20132012","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"key":"1370_CR33","unstructured":"Li YQ, Nie FP, Huang H, Huang JZ (2015) Large-scale multiview spectral clustering via bipartite graph. In: Proceedings of the Twenty-Ninth AAAI Conference on ArtificialIntelligence, pp. 2750\u20132756"},{"key":"1370_CR34","unstructured":"Niu D, Dy J, Jordan M (2010) Multiple non-redundant spectral clustering views. In: International Conference on Machine\u00a0Learning, pp 831\u2013838"},{"key":"1370_CR35","unstructured":"Nie F, Li J, Li X (2016) Parameter-free auto-weighted multiple graph learning: a framework for multiview clustering and semisupervised classification. In: The 25th international joint conference on artificial intelligence (IJCAI). New York,\u00a0p. 1881\u20131887"},{"key":"1370_CR36","doi-asserted-by":"crossref","unstructured":"Chaudhuri K, Kakade S. M, Livescu K, Sridharan K (2009) Multi-view clustering via canonical correlation analysis. In: ICML, pp 14\u201318","DOI":"10.1145\/1553374.1553391"},{"issue":"6","key":"1370_CR37","doi-asserted-by":"publisher","first-page":"1438","DOI":"10.1109\/TSMCB.2009.2039566","volume":"40","author":"T Xia","year":"2010","unstructured":"Xia T, Tao D, Mei T, Zhang Y (2010) Multiview spectral embedding. IEEE Trans Syst Man Cybern B Cybern 40(6):1438\u20131446","journal-title":"IEEE Trans Syst Man Cybern B Cybern"},{"key":"1370_CR38","doi-asserted-by":"crossref","unstructured":"Li Y, Nie F, Huang H, Huang J (2015) Large-scale multi-view spectral clustering via bipartite graph. In: Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, pp 2750\u20132756","DOI":"10.1609\/aaai.v29i1.9598"},{"key":"1370_CR39","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.neunet.2017.01.001","volume":"88","author":"X Fang","year":"2017","unstructured":"Fang X, Xu Y, Li X, Lai Z, Teng S, Fei L (2017) Orthogonal self-guided similarity preserving projection for classification and clustering. Neural Netw 88:1\u20138","journal-title":"Neural Netw"},{"issue":"3","key":"1370_CR40","doi-asserted-by":"publisher","first-page":"1501","DOI":"10.1109\/TIP.2017.2754939","volume":"27","author":"F Nie","year":"2018","unstructured":"Nie F, Cai G, Li J, Li X (2018) Auto-weighted multi-view learning for image clustring and semi-supervised classification. IEEE Trans Image Process 27(3):1501\u20131511","journal-title":"IEEE Trans Image Process"},{"key":"1370_CR41","unstructured":"Hong M, Luo Z, Razaviyayn M (2014) Convergence analysis of ADMM for a family of nonconvex problems. In: Proceedings of conference neutral information processing systems"},{"key":"1370_CR42","unstructured":"Hong M, Luo Z (2012) On the linear convergence of the alternating direction method of multipliers. arXiv:1208.3922"},{"issue":"1","key":"1370_CR43","first-page":"1","volume":"3","author":"S Boyd","year":"2011","unstructured":"Boyd S, Parikh N, Chu E, Peleato B, Eckstein J (2011) Distributed optimization and statistical learning via the alternating direction method of multipliers. Found TrendsR Mach Learn 3(1):1\u2013122","journal-title":"Found TrendsR Mach Learn"},{"key":"1370_CR44","doi-asserted-by":"crossref","unstructured":"Zhang Y, Jiang Z, Davis L (2013) Learning structured low-rank representations for image classification. In: Proc. IEEE Conf. computer vision and pattern recognition, pp 23\u201328","DOI":"10.1109\/CVPR.2013.93"},{"issue":"3","key":"1370_CR45","doi-asserted-by":"publisher","first-page":"1173","DOI":"10.1109\/TIP.2016.2623487","volume":"26","author":"P Zhou","year":"2017","unstructured":"Zhou P, Zhang C, Lin Z (2017) Bilevel model based discriminative dictionary learning for recognition. IEEE Trans Image Process 26(3):1173\u20131187","journal-title":"IEEE Trans Image Process"},{"issue":"3","key":"1370_CR46","doi-asserted-by":"publisher","first-page":"572","DOI":"10.1109\/TMM.2012.2234731","volume":"15","author":"Y Yang","year":"2013","unstructured":"Yang Y, Song J, Huang Z, Ma Z, Sebe N, Hauptmann AG (2013) Multi-feature fusion via hierarchical regression for multimedia analysis. IEEE Trans Multimedia 15(3):572\u2013581","journal-title":"IEEE Trans Multimedia"},{"issue":"2","key":"1370_CR47","doi-asserted-by":"publisher","first-page":"143","DOI":"10.1007\/s11263-009-0252-y","volume":"85","author":"Y Jae Lee","year":"2009","unstructured":"Jae Lee Y, Grauman K (2009) Foreground focus: unsupervised learning from partially matching images. Int J Comput Vision 85(2):143\u2013166","journal-title":"Int J Comput Vision"},{"issue":"9","key":"1370_CR48","doi-asserted-by":"publisher","first-page":"4283","DOI":"10.1109\/TIP.2017.2717191","volume":"26","author":"H Tao","year":"2017","unstructured":"Tao H, Hou C, Nie F, Zhu J, Yi D (2017) Scalable multi-view semi-supervised classification via adaptive regression. IEEE Trans Image Process 26(9):4283\u20134296","journal-title":"IEEE Trans Image Process"}],"container-title":["International Journal of Machine Learning and Cybernetics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13042-021-01370-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s13042-021-01370-0\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13042-021-01370-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,1,6]],"date-time":"2023-01-06T20:28:35Z","timestamp":1673036915000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s13042-021-01370-0"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,8,6]]},"references-count":48,"journal-issue":{"issue":"10","published-print":{"date-parts":[[2021,10]]}},"alternative-id":["1370"],"URL":"https:\/\/doi.org\/10.1007\/s13042-021-01370-0","relation":{},"ISSN":["1868-8071","1868-808X"],"issn-type":[{"type":"print","value":"1868-8071"},{"type":"electronic","value":"1868-808X"}],"subject":[],"published":{"date-parts":[[2021,8,6]]},"assertion":[{"value":"9 October 2020","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"23 June 2021","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"6 August 2021","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}