{"id":"https://openalex.org/W2013564878","doi":"https://doi.org/10.1109/cvpr.2010.5539925","title":"Pareto discriminant analysis","display_name":"Pareto discriminant analysis","publication_year":2010,"publication_date":"2010-06-01","ids":{"openalex":"https://openalex.org/W2013564878","doi":"https://doi.org/10.1109/cvpr.2010.5539925","mag":"2013564878"},"language":"en","primary_location":{"id":"doi:10.1109/cvpr.2010.5539925","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2010.5539925","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition","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/A5057948105","display_name":"Karim T. Abou\u2013Moustafa","orcid":"https://orcid.org/0000-0003-4486-3804"},"institutions":[{"id":"https://openalex.org/I5023651","display_name":"McGill University","ror":"https://ror.org/01pxwe438","country_code":"CA","type":"education","lineage":["https://openalex.org/I5023651"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Karim T. Abou-Moustafa","raw_affiliation_strings":["Centre of Intelligent Machines, McGill University, Canada","Centre of Intelligent Machines, McGill University"],"affiliations":[{"raw_affiliation_string":"Centre of Intelligent Machines, McGill University, Canada","institution_ids":["https://openalex.org/I5023651"]},{"raw_affiliation_string":"Centre of Intelligent Machines, McGill University","institution_ids":["https://openalex.org/I5023651"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108127869","display_name":"Fernando De la Torre","orcid":null},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Fernando de la Torre","raw_affiliation_strings":["Robotics Institute, Carnegie Mellon University, USA","The Robotics Institute Carnegie-Mellon University"],"affiliations":[{"raw_affiliation_string":"Robotics Institute, Carnegie Mellon University, USA","institution_ids":["https://openalex.org/I74973139"]},{"raw_affiliation_string":"The Robotics Institute Carnegie-Mellon University","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5109219829","display_name":"Frank P. Ferrie","orcid":null},"institutions":[{"id":"https://openalex.org/I5023651","display_name":"McGill University","ror":"https://ror.org/01pxwe438","country_code":"CA","type":"education","lineage":["https://openalex.org/I5023651"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Frank P. Ferrie","raw_affiliation_strings":["Centre of Intelligent Machines, McGill University, Canada","Centre of Intelligent Machines, McGill University"],"affiliations":[{"raw_affiliation_string":"Centre of Intelligent Machines, McGill University, Canada","institution_ids":["https://openalex.org/I5023651"]},{"raw_affiliation_string":"Centre of Intelligent Machines, McGill University","institution_ids":["https://openalex.org/I5023651"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5057948105"],"corresponding_institution_ids":["https://openalex.org/I5023651"],"apc_list":null,"apc_paid":null,"fwci":2.56089891,"has_fulltext":false,"cited_by_count":25,"citation_normalized_percentile":{"value":0.89979434,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"3602","last_page":"3609"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10057","display_name":"Face and Expression Recognition","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T11871","display_name":"Advanced Statistical Methods and Models","score":0.9925000071525574,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9760000109672546,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/pairwise-comparison","display_name":"Pairwise comparison","score":0.7171353101730347},{"id":"https://openalex.org/keywords/linear-discriminant-analysis","display_name":"Linear discriminant analysis","score":0.6449731588363647},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.6220360994338989},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5374930500984192},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.49680307507514954},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.47389450669288635},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.4174741804599762},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.3209792673587799},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.22195863723754883}],"concepts":[{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.7171353101730347},{"id":"https://openalex.org/C69738355","wikidata":"https://www.wikidata.org/wiki/Q1228929","display_name":"Linear discriminant analysis","level":2,"score":0.6449731588363647},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.6220360994338989},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5374930500984192},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.49680307507514954},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47389450669288635},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.4174741804599762},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3209792673587799},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.22195863723754883}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cvpr.2010.5539925","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2010.5539925","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7699999809265137,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321747","display_name":"Fonds Qu\u00e9b\u00e9cois de la Recherche sur la Nature et les Technologies","ror":"https://ror.org/00b9f9778"},{"id":"https://openalex.org/F4320334593","display_name":"Natural Sciences and Engineering Research Council of Canada","ror":"https://ror.org/01h531d29"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W84799978","https://openalex.org/W1480487340","https://openalex.org/W1985809919","https://openalex.org/W2001619934","https://openalex.org/W2053016878","https://openalex.org/W2080400971","https://openalex.org/W2084812512","https://openalex.org/W2104448323","https://openalex.org/W2111574755","https://openalex.org/W2116019577","https://openalex.org/W2119168257","https://openalex.org/W2123921160","https://openalex.org/W2124083668","https://openalex.org/W2129302305","https://openalex.org/W2135346934","https://openalex.org/W2137611320","https://openalex.org/W2146820706","https://openalex.org/W2152010828","https://openalex.org/W2158114849","https://openalex.org/W2164552042","https://openalex.org/W2170285963","https://openalex.org/W2171849959","https://openalex.org/W2314766113","https://openalex.org/W2403035479","https://openalex.org/W2475432418","https://openalex.org/W2493109494","https://openalex.org/W2615258659","https://openalex.org/W2999575747","https://openalex.org/W4302557773","https://openalex.org/W6603561811","https://openalex.org/W6721461273"],"related_works":["https://openalex.org/W2339674921","https://openalex.org/W1572802059","https://openalex.org/W1997472478","https://openalex.org/W2743258233","https://openalex.org/W2311479510","https://openalex.org/W2804842029","https://openalex.org/W2104912729","https://openalex.org/W43316407","https://openalex.org/W1905704307","https://openalex.org/W2586441539"],"abstract_inverted_index":{"Linear":[0],"Discriminant":[1,94],"Analysis":[2,95],"(LDA)":[3],"is":[4,179,199],"a":[5,106,110,120,180],"popular":[6],"tool":[7],"for":[8,27],"multiclass":[9,44,117,142,236],"discriminative":[10],"dimensionality":[11],"reduction.":[12],"However,":[13],"LDA":[14],"suffers":[15],"from":[16,169,217],"two":[17,88],"major":[18],"problems:":[19],"(1)":[20],"It":[21],"only":[22],"optimizes":[23],"the":[24,28,47,53,64,73,82,103,116,127,147,162,173,196,218],"Bayes":[25],"error":[26],"case":[29,163],"of":[30,49,102,122,136,149,228,238],"unimodal":[31],"Gaussian":[32,108],"classes":[33,77,104,166],"with":[34,109,232],"equal":[35],"covariances":[36],"(assuming":[37],"full":[38],"rank":[39],"matrices)":[40],"and,":[41],"(2)":[42],"The":[43],"extension":[45],"maximizes":[46,156],"sum":[48,148],"pairwise":[50,61,123,128,150,158],"distances":[51,151],"between":[52,63,76,130,152],"classes,":[54,153],"and":[55,195,214,223,234],"does":[56],"not":[57],"\"simultaneously\"":[58],"maximize":[59,146],"each":[60,101,157,170],"distance":[62,129],"classes.":[65,132],"This":[66],"typically":[67,145],"results":[68,206,225],"in":[69,72,81,172,226],"serious":[70],"overlapping":[71],"projected":[74],"space":[75],"that":[78,144,164],"are":[79,167],"\"close\"":[80],"input":[83],"space.":[84,176],"To":[85],"solve":[86],"these":[87],"problems,":[89,143],"this":[90],"paper":[91],"proposes":[92],"Pareto":[93],"(PARDA).":[96],"Firstly,":[97],"PARDA":[98,114,154,178,229],"explicitly":[99],"models":[100],"as":[105],"multidimensional":[107],"sample":[111],"covariance.":[112],"Secondly,":[113],"decomposes":[115],"problem":[118,183],"to":[119,141,201],"set":[121],"objective":[124,192],"functions":[125,193],"representing":[126],"different":[131],"Unlike":[133],"existing":[134],"extensions":[135,237],"Fisher":[137],"discriminant":[138],"analysis":[139],"(FDA)":[140],"simultaneously":[155,185],"distance,":[159],"thus":[160],"encouraging":[161,224],"all":[165],"equidistant":[168],"other":[171],"lower":[174],"dimensional":[175],"Solving":[177],"multiobjective":[181],"optimization":[182],"-":[184,194],"optimizing":[186],"more":[187],"than":[188],"one,":[189],"possibly":[190],"conflicting,":[191],"resulting":[197],"solution":[198],"known":[200],"be":[202],"\"Pareto":[203],"Optimal\".":[204],"Experimental":[205],"on":[207],"synthetic":[208],"data,":[209],"several":[210],"image":[211],"data":[212,215],"sets":[213,216],"UCI":[219],"repository":[220],"show":[221],"positive":[222],"favor":[227],"when":[230],"compared":[231],"standard":[233],"state-of-the-art":[235],"LDA.":[239]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":2},{"year":2014,"cited_by_count":2},{"year":2013,"cited_by_count":5},{"year":2012,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}