{"id":"https://openalex.org/W2125781844","doi":"https://doi.org/10.1109/cvpr.2001.990453","title":"Bayesian learning of sparse classifiers","display_name":"Bayesian learning of sparse classifiers","publication_year":2005,"publication_date":"2005-08-25","ids":{"openalex":"https://openalex.org/W2125781844","doi":"https://doi.org/10.1109/cvpr.2001.990453","mag":"2125781844"},"language":"en","primary_location":{"id":"doi:10.1109/cvpr.2001.990453","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2001.990453","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5026826555","display_name":"M\u00e1rio A. T. Figueiredo","orcid":"https://orcid.org/0000-0002-0970-7745"},"institutions":[{"id":"https://openalex.org/I4210120471","display_name":"Instituto de Telecomunica\u00e7\u00f5es","ror":"https://ror.org/02ht4fk33","country_code":"PT","type":"nonprofit","lineage":["https://openalex.org/I4210120471"]},{"id":"https://openalex.org/I4387152517","display_name":"Instituto Superior T\u00e9cnico","ror":"https://ror.org/03db2by73","country_code":null,"type":"education","lineage":["https://openalex.org/I141596103","https://openalex.org/I4387152517"]}],"countries":["PT"],"is_corresponding":true,"raw_author_name":"M.A.T. Figueiredo","raw_affiliation_strings":["Institute de Telecomunica\u00e7\u00f5es, Instituto Superior T\u00e9cnico, Lisboa, Portugal","Instituto de Telecomunicagoes, Instituto Superior Tecnico, Lisbon, Portugal"],"affiliations":[{"raw_affiliation_string":"Institute de Telecomunica\u00e7\u00f5es, Instituto Superior T\u00e9cnico, Lisboa, Portugal","institution_ids":["https://openalex.org/I4210120471","https://openalex.org/I4387152517"]},{"raw_affiliation_string":"Instituto de Telecomunicagoes, Instituto Superior Tecnico, Lisbon, Portugal","institution_ids":["https://openalex.org/I4210120471","https://openalex.org/I4387152517"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100613677","display_name":"Anil K. Jain","orcid":"https://orcid.org/0000-0002-6369-6995"},"institutions":[{"id":"https://openalex.org/I87216513","display_name":"Michigan State University","ror":"https://ror.org/05hs6h993","country_code":"US","type":"education","lineage":["https://openalex.org/I87216513"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"A.K. Jain","raw_affiliation_strings":["Department of Computer Science and Engineering, Michigan State University, East Lansing, MI, USA","Michigan State University"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Michigan State University, East Lansing, MI, USA","institution_ids":["https://openalex.org/I87216513"]},{"raw_affiliation_string":"Michigan State University","institution_ids":["https://openalex.org/I87216513"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5026826555"],"corresponding_institution_ids":["https://openalex.org/I4210120471","https://openalex.org/I4387152517"],"apc_list":null,"apc_paid":null,"fwci":11.8741,"has_fulltext":false,"cited_by_count":65,"citation_normalized_percentile":{"value":0.98497039,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"1","issue":null,"first_page":"I","last_page":"35"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9983999729156494,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9983999729156494,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9980000257492065,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11236","display_name":"Control Systems and Identification","score":0.9961000084877014,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6740961670875549},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6674402952194214},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.618018388748169},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5272036194801331},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5263594388961792}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6740961670875549},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6674402952194214},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.618018388748169},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5272036194801331},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5263594388961792}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/cvpr.2001.990453","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2001.990453","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.186.2705","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.186.2705","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.lx.it.pt/%7Emtf/Figueiredo_Jain_CVPR_2001.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.23.2864","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.23.2864","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://red.lx.it.pt/~mtf/FigueiredoJainCVPR2001.ps.gz","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.96.2336","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.96.2336","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.tsi.enst.fr/~campedel/Biblio/FeatureSelection/FigueiredoJain_2001.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":43,"referenced_works":["https://openalex.org/W109189503","https://openalex.org/W1528905581","https://openalex.org/W1553407966","https://openalex.org/W1554663460","https://openalex.org/W1563088657","https://openalex.org/W1567512734","https://openalex.org/W1594031697","https://openalex.org/W1657213141","https://openalex.org/W1965026065","https://openalex.org/W1986931325","https://openalex.org/W1988520084","https://openalex.org/W2002355073","https://openalex.org/W2011873184","https://openalex.org/W2049633694","https://openalex.org/W2067633806","https://openalex.org/W2107710506","https://openalex.org/W2108306139","https://openalex.org/W2112545207","https://openalex.org/W2117063635","https://openalex.org/W2117812871","https://openalex.org/W2119862467","https://openalex.org/W2129869373","https://openalex.org/W2132549764","https://openalex.org/W2135046866","https://openalex.org/W2135338737","https://openalex.org/W2137512539","https://openalex.org/W2140499889","https://openalex.org/W2143956139","https://openalex.org/W2146766088","https://openalex.org/W2148603752","https://openalex.org/W2156706175","https://openalex.org/W3015463134","https://openalex.org/W3085162807","https://openalex.org/W3129711340","https://openalex.org/W4246701766","https://openalex.org/W4251699153","https://openalex.org/W4298876635","https://openalex.org/W4301861531","https://openalex.org/W4388297464","https://openalex.org/W6676234565","https://openalex.org/W6676930901","https://openalex.org/W6679262826","https://openalex.org/W6680216138"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W3046775127","https://openalex.org/W3107602296","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W4364306694","https://openalex.org/W4312192474","https://openalex.org/W2033914206","https://openalex.org/W4283697347"],"abstract_inverted_index":{"Bayesian":[0,78],"approaches":[1],"to":[2,25,61,80],"supervised":[3],"learning":[4,81],"use":[5,35],"priors":[6,13],"on":[7,40],"the":[8,41,44,63,67,72,91,103,108,126,138],"classifier":[9],"parameters.":[10],"However,":[11],"few":[12],"aim":[14],"at":[15],"achieving":[16],"\"sparse\"":[17],"classifiers,":[18],"where":[19],"irrelevant/redundant":[20],"parameters":[21,64,89],"are":[22],"automatically":[23],"set":[24],"zero.":[26],"Two":[27],"well-known":[28],"ways":[29],"of":[30,69,71,93,102,110,125],"obtaining":[31],"sparse":[32,82],"classifiers":[33,83],"are:":[34],"a":[36,52,77,99,111],"zero-mean":[37],"Laplacian":[38,53,104],"prior":[39,54],"parameters,":[42],"and":[43],"\"support":[45],"vector":[46],"machine\"":[47],"(SVM).":[48],"Whether":[49],"one":[50,58],"uses":[51],"or":[55],"an":[56,120],"SVM,":[57],"still":[59],"needs":[60],"specify/estimate":[62],"that":[65,130],"control":[66],"degree":[68,92],"sparseness":[70],"resulting":[73],"classifiers.":[74],"We":[75],"propose":[76],"approach":[79],"which":[84],"does":[85],"not":[86],"involve":[87],"any":[88],"controlling":[90],"sparseness.":[94],"This":[95],"is":[96,116],"achieved":[97],"by":[98,107,119],"hierarchical-Bayes":[100],"interpretation":[101],"prior,":[105],"followed":[106],"adoption":[109],"Jeffreys'":[112],"non-informative":[113],"hyper-prior":[114],"Implementation":[115],"carried":[117],"out":[118],"EM":[121],"algorithm.":[122],"Experimental":[123],"evaluation":[124],"proposed":[127],"method":[128],"shows":[129],"it":[131],"performs":[132],"competitively":[133],"with":[134],"(often":[135],"better":[136],"than)":[137],"best":[139],"classification":[140],"techniques":[141],"available.":[142]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":3},{"year":2018,"cited_by_count":1},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":3},{"year":2012,"cited_by_count":2}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}