{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,7,7]],"date-time":"2024-07-07T23:43:06Z","timestamp":1720395786506},"reference-count":17,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2014,9,1]],"date-time":"2014-09-01T00:00:00Z","timestamp":1409529600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Neurocomputing"],"published-print":{"date-parts":[[2014,9]]},"DOI":"10.1016\/j.neucom.2013.09.057","type":"journal-article","created":{"date-parts":[[2014,3,31]],"date-time":"2014-03-31T15:57:23Z","timestamp":1396281443000},"page":"47-55","update-policy":"http:\/\/dx.doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":18,"special_numbering":"C","title":["Learning a generative classifier from label proportions"],"prefix":"10.1016","volume":"139","author":[{"given":"Kai","family":"Fan","sequence":"first","affiliation":[]},{"given":"Hongyi","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Songbai","family":"Yan","sequence":"additional","affiliation":[]},{"given":"Liwei","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Wensheng","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Jufu","family":"Feng","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"key":"10.1016\/j.neucom.2013.09.057_bib1","unstructured":"S. Marco, K. Morik, Learning from label proportions by optimizing cluster model selection, in: ECML PKDD 2011, vol. 6931, Part 3, 2011, pp. 349\u2013364."},{"key":"10.1016\/j.neucom.2013.09.057_bib2","doi-asserted-by":"crossref","unstructured":"Y. Bengio, P. Lamblin, D. Popovici, H. Larochelle, Greedy Layer-Wise Training of Deep Networks, NIPS, 2007, pp. 153\u2013160.","DOI":"10.7551\/mitpress\/7503.003.0024"},{"key":"10.1016\/j.neucom.2013.09.057_bib3","unstructured":"H. Kueck, N. de Freitas, Learning about individuals from group statistics, Uncertainty in Artif (UAI), AUAI Press, Arlington, Virginia, 2005, pp. 332\u2013339."},{"key":"10.1016\/j.neucom.2013.09.057_bib4","doi-asserted-by":"crossref","unstructured":"P.A. Wedin, Perturbation theory for pseudo-inverses, BIT Numer. Math. 13 (2), 1973, pp. 217\u2013232","DOI":"10.1007\/BF01933494"},{"key":"10.1016\/j.neucom.2013.09.057_bib5","unstructured":"Stefan Rueping. SVM classifier estimation from group probabilities, in: Proceedings of the 27th Annual International Conference on Machine Learning, ICML 2010, 2010."},{"issue":"October","key":"10.1016\/j.neucom.2013.09.057_bib6","first-page":"2349","article-title":"Estimating labels from label proportions","volume":"10","author":"Quadrianto","year":"2009","journal-title":"J. Mach. Learn. Res."},{"key":"10.1016\/j.neucom.2013.09.057_bib7","unstructured":"A. Smola, S.V.N. Vishwanathan, Q. Le, Bundle Methods for Machine Learning, NIPS 2007, 2007."},{"key":"10.1016\/j.neucom.2013.09.057_bib8","doi-asserted-by":"crossref","unstructured":"Y. Altun, A. Smola, Unifying divergence minimization and statistical inference via convex duality, in: Proceedings of Annual Conference on Computational Learning Theory, Lecture Notes in Computer Science, 2006, pp. 139\u2013153.","DOI":"10.1007\/11776420_13"},{"key":"10.1016\/j.neucom.2013.09.057_bib9","unstructured":"M. Carreira-Perpinan, G. Hinton, On contrastive divergence learning, in: 10th International Workshop on Artificial Intelligence and Statistics, AISTATS 2005, 2005."},{"key":"10.1016\/j.neucom.2013.09.057_bib10","unstructured":"G. Hinton, A Practical Guide to Training Restricted Boltzmann Machines, UTML TR. AUG, 003, 2003."},{"key":"10.1016\/j.neucom.2013.09.057_bib11","doi-asserted-by":"crossref","first-page":"1527","DOI":"10.1162\/neco.2006.18.7.1527","article-title":"A fast learning algorithm for deep belief nets","volume":"18","author":"Hinton","year":"2006","journal-title":"Neural Comput."},{"key":"10.1016\/j.neucom.2013.09.057_bib12","doi-asserted-by":"crossref","unstructured":"R. Salakhutdinov, I. Murray, On the Quantitative Analysis of Deep Belief Networks, ICML 2008.","DOI":"10.1145\/1390156.1390266"},{"key":"10.1016\/j.neucom.2013.09.057_bib13","unstructured":"A, Smola, S.V.N. Vishwanathan, Q. Le, Bundle Methods for Machine Learning, NIPS 2007."},{"key":"10.1016\/j.neucom.2013.09.057_bib14","series-title":"Statistical Learning Theory","author":"Vapnik","year":"1998"},{"key":"10.1016\/j.neucom.2013.09.057_bib15","series-title":"Matrix Theory: Basic Results and Techniques","author":"Fuzhen","year":"2011"},{"key":"10.1016\/j.neucom.2013.09.057_bib16","doi-asserted-by":"crossref","unstructured":"C. Dwork, Differential Privacy, in: ICALP, 2006, pp. 1\u201312.","DOI":"10.1007\/11787006_1"},{"key":"10.1016\/j.neucom.2013.09.057_bib17","doi-asserted-by":"crossref","unstructured":"D. Kifer, Attacks on Privacy and deFinetti\u05f3s Theorem. ACM SIGMOD 09, Providence, RI, USA, 2009.","DOI":"10.1145\/1559845.1559861"}],"container-title":["Neurocomputing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0925231214003671?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0925231214003671?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2023,7,11]],"date-time":"2023-07-11T17:44:31Z","timestamp":1689097471000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0925231214003671"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2014,9]]},"references-count":17,"alternative-id":["S0925231214003671"],"URL":"https:\/\/doi.org\/10.1016\/j.neucom.2013.09.057","relation":{},"ISSN":["0925-2312"],"issn-type":[{"value":"0925-2312","type":"print"}],"subject":[],"published":{"date-parts":[[2014,9]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Learning a generative classifier from label proportions","name":"articletitle","label":"Article Title"},{"value":"Neurocomputing","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.neucom.2013.09.057","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"Copyright \u00a9 2014 Elsevier B.V. All rights reserved.","name":"copyright","label":"Copyright"}]}}