{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,16]],"date-time":"2025-10-16T06:55:32Z","timestamp":1760597732850,"version":"3.37.3"},"reference-count":34,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2017,1,21]],"date-time":"2017-01-21T00:00:00Z","timestamp":1484956800000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61273251","61673220"],"award-info":[{"award-number":["61273251","61673220"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Neural Process Lett"],"published-print":{"date-parts":[[2017,8]]},"DOI":"10.1007\/s11063-017-9579-5","type":"journal-article","created":{"date-parts":[[2017,1,21]],"date-time":"2017-01-21T03:31:16Z","timestamp":1484969476000},"page":"219-232","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Multiple Instance Learning via Semi-supervised Laplacian TSVM"],"prefix":"10.1007","volume":"46","author":[{"given":"Xizhan","family":"Gao","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Quansen","family":"Sun","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Haitao","family":"Xu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2017,1,21]]},"reference":[{"key":"9579_CR1","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1016\/S0004-3702(96)00034-3","volume":"89","author":"TG Dietterich","year":"1997","unstructured":"Dietterich TG, Lathrop RH (1997) Solving the multiple-instance problem with axis-parallel rectangles. Artif Intell 89:31\u201371","journal-title":"Artif Intell"},{"unstructured":"Maron O, Ratan AL (1998) Multiple-instance learning for natural scene classification. In: 15th international conference on machine learning. Morgan Kaufmann Publishers Inc., San Francisco, pp 341\u2013349","key":"9579_CR2"},{"key":"9579_CR3","first-page":"1073","volume":"14","author":"Q Zhang","year":"2002","unstructured":"Zhang Q, Goldman S (2002) Em-dd: an improved multiple instance learning technique. Adv Neural Inf Process Syst 14:1073\u20131080","journal-title":"Adv Neural Inf Process Syst"},{"unstructured":"Andrews S, Tsochantaridis I, Hofmann T (2003) Support vector machines for maultiple-instance learning, In: Advances in neural information processing systems 15, MIT Press, pp 561\u2013568","key":"9579_CR4"},{"unstructured":"Wang J, Zucker JD (2000) Solving the multi-instance problem: a lazy learning approach, ICML00, San Francisco, pp 1119\u20131125","key":"9579_CR5"},{"unstructured":"Ruffo G (2000) Learning single and multiple instance decision trees for computer security applications, Doctoral dissertation, Department of Computer Science, University of Turin, Torino","key":"9579_CR6"},{"unstructured":"Chevaleyre Y, Zucker JD (2001) A framework for learning rules from multiple instance data, ECML01. Freiburg, pp 49\u201360","key":"9579_CR7"},{"key":"9579_CR8","first-page":"913","volume":"5","author":"Y Chen","year":"2004","unstructured":"Chen Y, Wang JZ (2004) Image categorization by learning and reasoning with regions. J Mach Learn Res 5:913\u2013939","journal-title":"J Mach Learn Res"},{"unstructured":"Zhou ZH, Zhang ML (2003) Ensembles of multi-instance learners, ECML03. Croatia, Cavtat- Dubrovnik, pp 492\u2013502","key":"9579_CR9"},{"unstructured":"Xu X, Frank E (2004) Logistic regression and boosting for labeled bags of instances, PAKDD04. Sydney, pp 272\u2013281","key":"9579_CR10"},{"doi-asserted-by":"crossref","unstructured":"Ray S, Craven M (2005) Supervised versus multiple instance learning: an empirical comparison, ICML05. Bonn, pp 697\u2013704","key":"9579_CR11","DOI":"10.1145\/1102351.1102439"},{"unstructured":"Ramon J, Raedt LD (2000) Multi-instance neural networks. In: Proceedings of the ICML-2000 workshop on attribute-value and relational learning. Morgan Kaufmann Publishers, San Francisco, pp 53\u201360","key":"9579_CR12"},{"issue":"1","key":"9579_CR13","doi-asserted-by":"crossref","first-page":"555","DOI":"10.1007\/s10957-007-9343-5","volume":"137","author":"OL Mangasarian","year":"2008","unstructured":"Mangasarian OL, Wild EW (2008) Multiple instance classification via successive linear programming. J Optim Theory Appl 137(1):555\u2013568","journal-title":"J Optim Theory Appl"},{"unstructured":"Yang ZX, Deng NY (2009) Multi-instance support vector machine based on convex combination, In: The 8th international symposium on operations research and its applications (ISORA09), pp 481\u2013487","key":"9579_CR14"},{"key":"9579_CR15","doi-asserted-by":"crossref","first-page":"1063","DOI":"10.1016\/j.procs.2013.05.135","volume":"17","author":"Q Zhang","year":"2013","unstructured":"Zhang Q, Tian Y, Liu D (2013) Nonparallel support vector machines for multiple-instance learning. Procedia Comput Sci 17:1063\u20131072","journal-title":"Procedia Comput Sci"},{"key":"9579_CR16","doi-asserted-by":"crossref","first-page":"233","DOI":"10.1016\/j.amc.2014.05.016","volume":"241","author":"Z Qi","year":"2014","unstructured":"Qi Z, Tian YJ, Yu XD, Shi Y (2014) A multi-instance learning algorithm based on nonparallel classifier. Appl Math Comput 241:233\u2013241","journal-title":"Appl Math Comput"},{"key":"9579_CR17","doi-asserted-by":"crossref","first-page":"8004","DOI":"10.1038\/srep08004","volume":"5","author":"S Bandyopadhyay","year":"2015","unstructured":"Bandyopadhyay S, Ghosh D, Mitra R (2015) MBSTAR: multiple instance learning for predicting specific functional binding sites in microRNA targets. Sci Rep 5:8004\u20138004","journal-title":"Sci Rep"},{"issue":"5","key":"9579_CR18","doi-asserted-by":"crossref","first-page":"669","DOI":"10.1109\/TCYB.2013.2265601","volume":"44","author":"R Hong","year":"2014","unstructured":"Hong R, Wang M, Gao Y et al (2014) Image annotation by multiple-instance learning with discriminative feature mapping and selection. IEEE Trans Cybern 44(5):669\u2013680","journal-title":"IEEE Trans Cybern"},{"key":"9579_CR19","first-page":"1121","volume":"1","author":"J Bi","year":"2005","unstructured":"Bi J, Chen Y, Wang JZ (2005) A sparse support vector machine approach to region-based image categorization. Cvpr 1:1121\u20131128","journal-title":"Cvpr"},{"issue":"4","key":"9579_CR20","doi-asserted-by":"crossref","first-page":"358","DOI":"10.1016\/j.apnum.2009.05.013","volume":"60","author":"OE Kundakcioglu","year":"2010","unstructured":"Kundakcioglu OE, Seref O, Pardalos PM (2010) Multiple instance learning via margin maximization. Appl Numer Math 60(4):358\u2013369","journal-title":"Appl Numer Math"},{"issue":"2","key":"9579_CR21","doi-asserted-by":"crossref","first-page":"135","DOI":"10.1007\/s10489-005-5602-z","volume":"22","author":"ZH Zhou","year":"2005","unstructured":"Zhou ZH, Jiang K, Li M (2005) Multi-instance learning based web mining. Appl Intell 22(2):135\u2013147","journal-title":"Appl Intell"},{"key":"9579_CR22","first-page":"368","volume":"11","author":"KP Bennett","year":"1999","unstructured":"Bennett KP, Demiriz A (1999) Semi-supervised support vector machines. Proc Neural Inf Process Syst 11:368\u2013374","journal-title":"Proc Neural Inf Process Syst"},{"issue":"1","key":"9579_CR23","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1080\/10556780108805809","volume":"15","author":"G Fung","year":"2000","unstructured":"Fung G, Mangasarian OL (2000) Semi-supervised support vector machines for unlabeled data classification. Optim Methods Softw 15(1):29\u201344","journal-title":"Optim Methods Softw"},{"key":"9579_CR24","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"},{"issue":"11","key":"9579_CR25","doi-asserted-by":"crossref","first-page":"46","DOI":"10.1016\/j.neunet.2012.07.011","volume":"35","author":"Z Qi","year":"2012","unstructured":"Qi Z, Tian Y, Yong S (2012) Laplacian twin support vector machine for semi-supervised classification. Neural Netw 35(11):46\u201353","journal-title":"Neural Netw"},{"unstructured":"Yang Z, Xu Y (2015) Laplacian twin parametric-margin support vector machine for semi-supervised classification. Neurocomputing 171(C):325\u2013334","key":"9579_CR26"},{"issue":"3","key":"9579_CR27","doi-asserted-by":"crossref","first-page":"459","DOI":"10.1007\/s13042-013-0183-3","volume":"5","author":"WJ Chen","year":"2014","unstructured":"Chen WJ, Shao YH, Hong N (2014) Laplacian smooth twin support vector machine for semi-supervised classification. Int J Mach Learn Cybern 5(3):459\u2013468","journal-title":"Int J Mach Learn Cybern"},{"doi-asserted-by":"crossref","unstructured":"Zhou ZH, Xu JM (2007) On the relation between multi-instance learning and semi-supervised learning, ICML\u201907. In: Proceedings of the 24th international conference on machine learning, pp 1167\u20131174","key":"9579_CR28","DOI":"10.1145\/1273496.1273643"},{"doi-asserted-by":"crossref","unstructured":"Rahmani R, Goldman SA (2006) MISSL: multiple-instance semi-supervised learning. In: Proceedings of the international conference on machine learning (ICML). pp 705\u2013712","key":"9579_CR29","DOI":"10.1145\/1143844.1143933"},{"key":"9579_CR30","doi-asserted-by":"crossref","first-page":"546","DOI":"10.1016\/j.asoc.2016.07.003","volume":"48","author":"XZ Gao","year":"2016","unstructured":"Gao XZ, Fan LY, Xu HT (2016) A novel method for classification of matrix data using twin multiple rank SMMs. Appl Soft Comput 48:546\u2013562","journal-title":"Appl Soft Comput"},{"issue":"1","key":"9579_CR31","doi-asserted-by":"crossref","first-page":"555","DOI":"10.1007\/s10957-007-9343-5","volume":"137","author":"OL Mangasarian","year":"2008","unstructured":"Mangasarian OL, Wild EW (2008) Multiple instance classification via successive linear programming. J Optim Theory Appl 137(1):555\u2013568","journal-title":"J Optim Theory Appl"},{"unstructured":"Murphy PM, Aha DW Uci machine learning repository, www.ics.uci.edu\/mlearn\/mlrepository.html","key":"9579_CR32"},{"unstructured":"http:\/\/www.cs.columbia.edu\/andrews\/mil\/datasets.html","key":"9579_CR33"},{"doi-asserted-by":"crossref","unstructured":"Nie FP, Wang XQ et al. (2016) The Constrained Laplacian Rank Algorithm for graph-based clustering. In: Proceedings of the 13th AAAI conference on artificial intelligence (AAAI-16)","key":"9579_CR34","DOI":"10.1609\/aaai.v30i1.10302"}],"container-title":["Neural Processing Letters"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s11063-017-9579-5\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11063-017-9579-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11063-017-9579-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,7,22]],"date-time":"2022-07-22T11:14:17Z","timestamp":1658488457000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s11063-017-9579-5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,1,21]]},"references-count":34,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2017,8]]}},"alternative-id":["9579"],"URL":"https:\/\/doi.org\/10.1007\/s11063-017-9579-5","relation":{},"ISSN":["1370-4621","1573-773X"],"issn-type":[{"type":"print","value":"1370-4621"},{"type":"electronic","value":"1573-773X"}],"subject":[],"published":{"date-parts":[[2017,1,21]]}}}