{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,13]],"date-time":"2025-10-13T19:56:17Z","timestamp":1760385377879},"reference-count":23,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2014,9,24]],"date-time":"2014-09-24T00:00:00Z","timestamp":1411516800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Neural Comput &amp; Applic"],"published-print":{"date-parts":[[2016,1]]},"DOI":"10.1007\/s00521-014-1710-1","type":"journal-article","created":{"date-parts":[[2014,9,23]],"date-time":"2014-09-23T23:18:52Z","timestamp":1411514332000},"page":"185-196","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":17,"title":["Variational Bayesian extreme learning machine"],"prefix":"10.1007","volume":"27","author":[{"given":"Yarui","family":"Chen","sequence":"first","affiliation":[]},{"given":"Jucheng","family":"Yang","sequence":"additional","affiliation":[]},{"given":"Chao","family":"Wang","sequence":"additional","affiliation":[]},{"given":"DongSun","family":"Park","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2014,9,24]]},"reference":[{"key":"1710_CR1","doi-asserted-by":"crossref","unstructured":"Huang GB, Zhu QY, Siew CK (2004) Extreme learning machine: a new learning scheme of feedforward neural networks. In: Proceedings of international joint conference on neural networks (IJCNN2004), vol 2, (Budapest, Hungary), pp 985\u2013990","DOI":"10.1109\/IJCNN.2004.1380068"},{"key":"1710_CR2","doi-asserted-by":"crossref","first-page":"489","DOI":"10.1016\/j.neucom.2005.12.126","volume":"70","author":"GB Huang","year":"2006","unstructured":"Huang GB, Zhu QY, Siew CK (2006) Extreme learning machine: theory and applications. Neurocomputing 70:489\u2013501","journal-title":"Neurocomputing"},{"issue":"3","key":"1710_CR3","doi-asserted-by":"crossref","first-page":"485","DOI":"10.1109\/tcbb.2007.1012","volume":"4","author":"R Zhang","year":"2007","unstructured":"Zhang R, Huang GB, Sundararajan N, Saratchandran P (2007) Multi-category classification using an extreme learning machine for microarray gene expression cancer diagnosis. IEEE\/ACM Trans Comput Biol Bioinf 4(3):485\u2013495","journal-title":"IEEE\/ACM Trans Comput Biol Bioinf"},{"issue":"1","key":"1710_CR4","doi-asserted-by":"crossref","first-page":"49","DOI":"10.1007\/s00521-011-0747-7","volume":"22","author":"CLC Mattos","year":"2013","unstructured":"Mattos CLC, Barreto GA (2013) ARTIE and MUSCLE models: building ensemble classifiers from fuzzy ART and SOM networks. Neural Comput Appl 22(1):49\u201361","journal-title":"Neural Comput Appl"},{"issue":"4","key":"1710_CR5","doi-asserted-by":"crossref","first-page":"879","DOI":"10.1109\/TNN.2006.875977","volume":"17","author":"GB Huang","year":"2006","unstructured":"Huang GB, Chen L, Siew CK (2006) Universal approximation using incremental constructive feedforward networks with random hidden nodes. IEEE Trans Neural Netw 17(4):879\u2013892","journal-title":"IEEE Trans Neural Netw"},{"issue":"16","key":"1710_CR6","doi-asserted-by":"crossref","first-page":"2369","DOI":"10.1016\/j.neucom.2006.02.013","volume":"69","author":"F Han","year":"2006","unstructured":"Han F, Huang DS (2006) Improved extreme learning machine for function approximation by encoding a priori information. Neurocomputing 69(16):2369\u20132373","journal-title":"Neurocomputing"},{"issue":"13","key":"1710_CR7","doi-asserted-by":"crossref","first-page":"3066","DOI":"10.1016\/j.neucom.2009.03.016","volume":"72","author":"X Tang","year":"2009","unstructured":"Tang X, Han M (2009) Partial Lanczos extreme learning machine for single-output regression problems. Neurocomputing 72(13):3066\u20133076","journal-title":"Neurocomputing"},{"issue":"10","key":"1710_CR8","doi-asserted-by":"crossref","first-page":"1906","DOI":"10.1016\/j.neucom.2010.01.020","volume":"73","author":"R Minhas","year":"2010","unstructured":"Minhas R, Baradarani A, Seifzadeh S, Jonathan Wu QM (2010) Human action recognition using extreme learning machine based on visual vocabularies. Neurocomputing 73(10):1906\u20131917","journal-title":"Neurocomputing"},{"issue":"10","key":"1710_CR9","doi-asserted-by":"crossref","first-page":"2160","DOI":"10.1016\/j.neucom.2010.02.001","volume":"73","author":"V Malathi","year":"2010","unstructured":"Malathi V, Marimuthu NS, Baskar S (2010) Intelligent approaches using support vector machine and extreme learning machine for transmission line protection. Neurocomputing 73(10):2160\u20132167","journal-title":"Neurocomputing"},{"issue":"3","key":"1710_CR10","doi-asserted-by":"crossref","first-page":"382","DOI":"10.1109\/LGRS.2006.873687","volume":"3","author":"CW Yeu","year":"2006","unstructured":"Yeu CW, Lim MH, Huang GB, Agarwal A, Ong YS (2006) A new machine learning paradigm for terrain reconstruction. Geosci Remote Sens Lett IEEE 3(3):382\u2013386","journal-title":"Geosci Remote Sens Lett IEEE"},{"key":"1710_CR11","doi-asserted-by":"crossref","first-page":"3460","DOI":"10.1016\/j.neucom.2007.10.008","volume":"71","author":"GB Huang","year":"2008","unstructured":"Huang GB, Chen L (2008) Enhanced random search based incremental extreme learning machine. Neurocomputing 71:3460\u20133468","journal-title":"Neurocomputing"},{"key":"1710_CR12","doi-asserted-by":"crossref","first-page":"61","DOI":"10.1613\/jair.251","volume":"4","author":"LK Saul","year":"1996","unstructured":"Saul LK, Jaakkola TS, Jordan MI (1996) Mean field theory for Sigmoid belief networks. J Artif Intell Res 4:61\u201376","journal-title":"J Artif Intell Res"},{"key":"1710_CR13","unstructured":"Yedidia JS, Freeman WT, Weiss Y (2001) Bethe free energy, Kikuchi approximations and belief propagation algorithms. Technical Report, TR-2001-16, Mitsubishi Electric Research Laboratories, Cambridge"},{"key":"1710_CR14","unstructured":"Yedidia JS, Freeman WT, Weiss Y (2001) Generalized belief propagation. In: Advances in neural information processing systems 13, vol 14. The MIT Press, Cambridge, pp 689\u2013695"},{"issue":"1\u20132","key":"1710_CR15","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1561\/2200000001","volume":"1","author":"MJ Wainwright","year":"2008","unstructured":"Wainwright MJ, Jordan MI (2008) Graphical models, exponential families, and variational inference. Found Trends Mach Learn 1(1\u20132):1\u2013305","journal-title":"Found Trends Mach Learn"},{"key":"1710_CR16","unstructured":"Wainwright MJ, Jaakkola TS, Willsky AS (2003) Tree-reweighted belief propagation algorithms and approximate ML estimation by pseudo-moment matching. In: Workshop on artificial intelligence and statistics"},{"key":"1710_CR17","unstructured":"Beal MJ (2003) Variational algorithms for approximate Bayesian inference. Ph.D. thesis, University of Cambridge"},{"key":"1710_CR18","first-page":"1","volume":"1","author":"MJ Beal","year":"2004","unstructured":"Beal MJ, Ghahramani Z (2004) Variational Bayesian learning of directed graphical models with hidden variables. Bayesian Anal 1:1\u201344","journal-title":"Bayesian Anal"},{"key":"1710_CR19","first-page":"453","volume-title":"Bayesian statistics","author":"MJ Beal","year":"2003","unstructured":"Beal MJ, Ghahramani Z (2003) The variational Bayesian EM algorithm for incomplete data: with application to scoring graphical model structures. In: Bernardo JM, Dawid AP, Berger JO, West M, Heckerman D, Bayarri MJ (eds) Bayesian statistics, vol 7. Oxford University Press, Oxford, pp 453\u2013464"},{"key":"1710_CR20","doi-asserted-by":"crossref","first-page":"183","DOI":"10.1023\/A:1007665907178","volume":"37","author":"MI Jordan","year":"1999","unstructured":"Jordan MI, Ghahramani Z, Jaakkola TS, Saul LK (1999) An introduction to variational methods for graphical models. Mach Learn 37:183\u2013233","journal-title":"Mach Learn"},{"key":"1710_CR21","unstructured":"Minka T (2005) Divergence measures and message passing. Technical report. MSR-TR-2005-173, Microsoft Research Ltd, Cambridge, UK"},{"key":"1710_CR22","unstructured":"Bishop CM (2006) Pattern recognition and machine learning. Springer, Berlin"},{"key":"1710_CR23","unstructured":"UIML Repository. http:\/\/archive.ics.uci.edu\/ml\/"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-014-1710-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s00521-014-1710-1\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-014-1710-1","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,8,15]],"date-time":"2019-08-15T09:15:02Z","timestamp":1565860502000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s00521-014-1710-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2014,9,24]]},"references-count":23,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2016,1]]}},"alternative-id":["1710"],"URL":"https:\/\/doi.org\/10.1007\/s00521-014-1710-1","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"value":"0941-0643","type":"print"},{"value":"1433-3058","type":"electronic"}],"subject":[],"published":{"date-parts":[[2014,9,24]]}}}