{"id":"https://openalex.org/W2553119673","doi":"https://doi.org/10.1109/mlsp.2016.7738819","title":"Multiclass SVM with graph path coding regularization for face classification","display_name":"Multiclass SVM with graph path coding regularization for face classification","publication_year":2016,"publication_date":"2016-09-01","ids":{"openalex":"https://openalex.org/W2553119673","doi":"https://doi.org/10.1109/mlsp.2016.7738819","mag":"2553119673"},"language":"en","primary_location":{"id":"doi:10.1109/mlsp.2016.7738819","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mlsp.2016.7738819","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE 26th International Workshop on Machine Learning for Signal Processing (MLSP)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5017257056","display_name":"Mingyuan Jiu","orcid":"https://orcid.org/0000-0002-4868-0709"},"institutions":[{"id":"https://openalex.org/I100532134","display_name":"Universit\u00e9 Claude Bernard Lyon 1","ror":"https://ror.org/029brtt94","country_code":"FR","type":"education","lineage":["https://openalex.org/I100532134","https://openalex.org/I203339264"]},{"id":"https://openalex.org/I113428412","display_name":"\u00c9cole Normale Sup\u00e9rieure de Lyon","ror":"https://ror.org/04zmssz18","country_code":"FR","type":"education","lineage":["https://openalex.org/I113428412","https://openalex.org/I203339264"]},{"id":"https://openalex.org/I4210103792","display_name":"Centre Max Weber","ror":"https://ror.org/026tf7535","country_code":"FR","type":"facility","lineage":["https://openalex.org/I113428412","https://openalex.org/I1294671590","https://openalex.org/I188626449","https://openalex.org/I203339264","https://openalex.org/I203339264","https://openalex.org/I203339264","https://openalex.org/I4210103792","https://openalex.org/I4405259976"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Mingyuan Jiu","raw_affiliation_strings":["Ens de Lyon, Univ Lyon 1, Lyon, France","\u00c9cole normale sup\u00e9rieure de Lyon"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ens de Lyon, Univ Lyon 1, Lyon, France","institution_ids":["https://openalex.org/I100532134","https://openalex.org/I113428412"]},{"raw_affiliation_string":"\u00c9cole normale sup\u00e9rieure de Lyon","institution_ids":["https://openalex.org/I113428412","https://openalex.org/I4210103792"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074166239","display_name":"Nelly Pustelnik","orcid":"https://orcid.org/0000-0001-7310-1927"},"institutions":[{"id":"https://openalex.org/I100532134","display_name":"Universit\u00e9 Claude Bernard Lyon 1","ror":"https://ror.org/029brtt94","country_code":"FR","type":"education","lineage":["https://openalex.org/I100532134","https://openalex.org/I203339264"]},{"id":"https://openalex.org/I113428412","display_name":"\u00c9cole Normale Sup\u00e9rieure de Lyon","ror":"https://ror.org/04zmssz18","country_code":"FR","type":"education","lineage":["https://openalex.org/I113428412","https://openalex.org/I203339264"]},{"id":"https://openalex.org/I4210103792","display_name":"Centre Max Weber","ror":"https://ror.org/026tf7535","country_code":"FR","type":"facility","lineage":["https://openalex.org/I113428412","https://openalex.org/I1294671590","https://openalex.org/I188626449","https://openalex.org/I203339264","https://openalex.org/I203339264","https://openalex.org/I203339264","https://openalex.org/I4210103792","https://openalex.org/I4405259976"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Nelly Pustelnik","raw_affiliation_strings":["Ens de Lyon, Univ Lyon 1, Lyon, France","\u00c9cole normale sup\u00e9rieure de Lyon"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ens de Lyon, Univ Lyon 1, Lyon, France","institution_ids":["https://openalex.org/I100532134","https://openalex.org/I113428412"]},{"raw_affiliation_string":"\u00c9cole normale sup\u00e9rieure de Lyon","institution_ids":["https://openalex.org/I113428412","https://openalex.org/I4210103792"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051381874","display_name":"M\u00e9riam Ch\u00e8bre","orcid":null},"institutions":[{"id":"https://openalex.org/I103084370","display_name":"Total (France)","ror":"https://ror.org/04sk34n56","country_code":"FR","type":"company","lineage":["https://openalex.org/I103084370"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Meriam Chebre","raw_affiliation_strings":["TOTAL SA, Direction Scientifique, Paris La Defense, France","TOTAL S.A"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"TOTAL SA, Direction Scientifique, Paris La Defense, France","institution_ids":["https://openalex.org/I103084370"]},{"raw_affiliation_string":"TOTAL S.A","institution_ids":["https://openalex.org/I103084370"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5107730385","display_name":"Stefan Janaqv","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Stefan Janaqv","raw_affiliation_strings":["LGI2P - EMA, Parc Scientifique Georges Besse, F-30035 Nimes, France","Laboratoire de G\u00e9nie Informatique et Ing\u00e9nierie de Production"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"LGI2P - EMA, Parc Scientifique Georges Besse, F-30035 Nimes, France","institution_ids":[]},{"raw_affiliation_string":"Laboratoire de G\u00e9nie Informatique et Ing\u00e9nierie de Production","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5068719482","display_name":"Philippe Ricoux","orcid":null},"institutions":[{"id":"https://openalex.org/I103084370","display_name":"Total (France)","ror":"https://ror.org/04sk34n56","country_code":"FR","type":"company","lineage":["https://openalex.org/I103084370"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Philippe Ricoux","raw_affiliation_strings":["TOTAL SA, Direction Scientifique, Paris La Defense, France","TOTAL S.A"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"TOTAL SA, Direction Scientifique, Paris La Defense, France","institution_ids":["https://openalex.org/I103084370"]},{"raw_affiliation_string":"TOTAL S.A","institution_ids":["https://openalex.org/I103084370"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9957000017166138,"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":0.9957000017166138,"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/T12676","display_name":"Machine Learning and ELM","score":0.9911999702453613,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9776999950408936,"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/computer-science","display_name":"Computer science","score":0.6390851736068726},{"id":"https://openalex.org/keywords/initialization","display_name":"Initialization","score":0.6002563238143921},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5853759050369263},{"id":"https://openalex.org/keywords/multiclass-classification","display_name":"Multiclass classification","score":0.5609242916107178},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5295066833496094},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4962933659553528},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.44530150294303894},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.41275760531425476},{"id":"https://openalex.org/keywords/directed-acyclic-graph","display_name":"Directed acyclic graph","score":0.4124467372894287},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3868448734283447},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.31485337018966675},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.27890002727508545}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6390851736068726},{"id":"https://openalex.org/C114466953","wikidata":"https://www.wikidata.org/wiki/Q6034165","display_name":"Initialization","level":2,"score":0.6002563238143921},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5853759050369263},{"id":"https://openalex.org/C123860398","wikidata":"https://www.wikidata.org/wiki/Q6934605","display_name":"Multiclass classification","level":3,"score":0.5609242916107178},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5295066833496094},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4962933659553528},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.44530150294303894},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.41275760531425476},{"id":"https://openalex.org/C74197172","wikidata":"https://www.wikidata.org/wiki/Q1195339","display_name":"Directed acyclic graph","level":2,"score":0.4124467372894287},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3868448734283447},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.31485337018966675},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.27890002727508545},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/mlsp.2016.7738819","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mlsp.2016.7738819","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE 26th International Workshop on Machine Learning for Signal Processing (MLSP)","raw_type":"proceedings-article"},{"id":"pmh:oai:HAL:hal-03583315v1","is_oa":false,"landing_page_url":"https://imt-mines-ales.hal.science/hal-03583315","pdf_url":null,"source":{"id":"https://openalex.org/S4306402512","display_name":"HAL (Le Centre pour la Communication Scientifique Directe)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1294671590","host_organization_name":"Centre National de la Recherche Scientifique","host_organization_lineage":["https://openalex.org/I1294671590"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"2016 IEEE 26th International Workshop on Machine Learning for Signal Processing (MLSP), Sep 2016, Vietri sul Mare, France. pp.1-6, &#x27E8;10.1109/MLSP.2016.7738819&#x27E9;","raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W144800816","https://openalex.org/W1798999207","https://openalex.org/W1946620893","https://openalex.org/W1970554427","https://openalex.org/W1976114481","https://openalex.org/W1992813007","https://openalex.org/W1995515386","https://openalex.org/W2006262045","https://openalex.org/W2015532756","https://openalex.org/W2028350189","https://openalex.org/W2072925128","https://openalex.org/W2077659054","https://openalex.org/W2120470041","https://openalex.org/W2124225314","https://openalex.org/W2126447117","https://openalex.org/W2132555912","https://openalex.org/W2135046866","https://openalex.org/W2138019504","https://openalex.org/W2139212933","https://openalex.org/W2151128232","https://openalex.org/W2153635508","https://openalex.org/W2157791002","https://openalex.org/W2159529227","https://openalex.org/W2172000360","https://openalex.org/W3004533406","https://openalex.org/W3025107628","https://openalex.org/W3104533819","https://openalex.org/W4288108337","https://openalex.org/W6637196363","https://openalex.org/W6677987708","https://openalex.org/W6678356451","https://openalex.org/W6678752900","https://openalex.org/W6682227116","https://openalex.org/W6682953061"],"related_works":["https://openalex.org/W2591058103","https://openalex.org/W2278160066","https://openalex.org/W2790464152","https://openalex.org/W2039745824","https://openalex.org/W2265622071","https://openalex.org/W2566282808","https://openalex.org/W3157224608","https://openalex.org/W2150314279","https://openalex.org/W2125602612","https://openalex.org/W2623163150"],"abstract_inverted_index":{"We":[0],"consider":[1],"the":[2,26,31,45,48,78,84,87,93,107,110,120,145],"problem":[3],"of":[4,86,92,128],"learning":[5],"graphs":[6],"in":[7,83],"a":[8,17,40,53,63,151],"sparse":[9,19,41,153],"multiclass":[10,70,142],"support":[11],"vector":[12],"machines":[13],"framework.":[14],"For":[15],"such":[16],"problem,":[18],"graph":[20,61,64,108,139],"penalty":[21,66],"is":[22,56,67,115],"useful":[23],"to":[24,69,105,150,156],"select":[25],"significant":[27],"features":[28,111],"and":[29,62,147],"interpret":[30],"results.":[32],"Classical":[33],"\u2113":[34,157],"<inf":[35,158],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[36,159],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">1</inf>":[37,160],"-norm":[38],"learns":[39],"solution":[42,154],"without":[43],"considering":[44],"structure":[46],"between":[47,109],"features.":[49,89],"In":[50],"this":[51],"paper,":[52],"structural":[54],"knowledge":[55],"encoded":[57],"as":[58],"directed":[59],"acyclic":[60],"path":[65],"incorporated":[68],"SVM.":[71],"The":[72,90,126],"learned":[73,88],"classifiers":[74],"not":[75],"only":[76],"improve":[77],"performance,":[79],"but":[80],"also":[81,148],"help":[82],"interpretation":[85],"performance":[91,146],"proposed":[94],"method":[95],"highly":[96],"depends":[97],"on":[98,132],"an":[99],"initialization":[100],"graph.":[101],"Two":[102],"generic":[103],"ways":[104],"initialize":[106],"are":[112],"considered:":[113],"one":[114,122],"built":[116],"from":[117],"similarities":[118],"while":[119],"other":[121],"uses":[123],"Graphical":[124],"Lasso.":[125],"experiments":[127],"face":[129],"classification":[130],"task":[131],"Extended":[133],"YaleB":[134],"database":[135],"verify":[136],"that:":[137],"i)":[138],"regularization":[140],"with":[141],"SVM":[143],"improves":[144],"leads":[149],"more":[152],"compared":[155],"-norm.":[161]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2018,"cited_by_count":2}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}