{"id":"https://openalex.org/W4245412002","doi":"https://doi.org/10.1109/icpr.2004.1334568","title":"Improved N-division output coding for multiclass learning problems","display_name":"Improved N-division output coding for multiclass learning problems","publication_year":2004,"publication_date":"2004-01-01","ids":{"openalex":"https://openalex.org/W4245412002","doi":"https://doi.org/10.1109/icpr.2004.1334568"},"language":"en","primary_location":{"id":"doi:10.1109/icpr.2004.1334568","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2004.1334568","pdf_url":null,"source":{"id":"https://openalex.org/S4363608750","display_name":"Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004.","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004.","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/A5101566090","display_name":"Jaepil Ko","orcid":"https://orcid.org/0000-0002-0625-092X"},"institutions":[{"id":"https://openalex.org/I3133298186","display_name":"Gumi University","ror":"https://ror.org/01tbn4j76","country_code":"KR","type":"education","lineage":["https://openalex.org/I3133298186"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jaepil Ko","raw_affiliation_strings":["CE Department, KIT, Gumi, Gyeongbuk, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CE Department, KIT, Gumi, Gyeongbuk, South Korea","institution_ids":["https://openalex.org/I3133298186"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100353130","display_name":"Eun-Ju Kim","orcid":"https://orcid.org/0009-0009-4260-2070"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Eunju Kim","raw_affiliation_strings":["ITA Department, NCA, Seoul, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ITA Department, NCA, Seoul, South Korea","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5049739329","display_name":"Hyeran Byun","orcid":"https://orcid.org/0000-0002-3082-3214"},"institutions":[{"id":"https://openalex.org/I193775966","display_name":"Yonsei University","ror":"https://ror.org/01wjejq96","country_code":"KR","type":"education","lineage":["https://openalex.org/I193775966"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Hyeran Byun","raw_affiliation_strings":["CS Department, Yonsei University, Seoul, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CS Department, Yonsei University, Seoul, South Korea","institution_ids":["https://openalex.org/I193775966"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.31004463,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"2","issue":null,"first_page":"470","last_page":"473 Vol.3"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9944000244140625,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9944000244140625,"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/T10057","display_name":"Face and Expression Recognition","score":0.9930999875068665,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.991599977016449,"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":0.659324586391449},{"id":"https://openalex.org/keywords/coding","display_name":"Coding (social sciences)","score":0.649347186088562},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5385881662368774},{"id":"https://openalex.org/keywords/multiclass-classification","display_name":"Multiclass classification","score":0.49434351921081543},{"id":"https://openalex.org/keywords/variable-length-code","display_name":"Variable-length code","score":0.45821231603622437},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.42448610067367554},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.4177211821079254},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.39391860365867615},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.33079794049263},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2675873637199402}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.659324586391449},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.649347186088562},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5385881662368774},{"id":"https://openalex.org/C123860398","wikidata":"https://www.wikidata.org/wiki/Q6934605","display_name":"Multiclass classification","level":3,"score":0.49434351921081543},{"id":"https://openalex.org/C60603091","wikidata":"https://www.wikidata.org/wiki/Q2981616","display_name":"Variable-length code","level":3,"score":0.45821231603622437},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.42448610067367554},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4177211821079254},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39391860365867615},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.33079794049263},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2675873637199402},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icpr.2004.1334568","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2004.1334568","pdf_url":null,"source":{"id":"https://openalex.org/S4363608750","display_name":"Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004.","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004.","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W1534477342","https://openalex.org/W1588401315","https://openalex.org/W1676820704","https://openalex.org/W1794117957","https://openalex.org/W1898476283","https://openalex.org/W1995358810","https://openalex.org/W2019575783","https://openalex.org/W2084812512","https://openalex.org/W2164641162","https://openalex.org/W2170892415","https://openalex.org/W2172000360","https://openalex.org/W3163638146","https://openalex.org/W4254721730","https://openalex.org/W6635310694","https://openalex.org/W6638226451","https://openalex.org/W6639651760","https://openalex.org/W6671611538","https://openalex.org/W6683984541","https://openalex.org/W6795924076"],"related_works":["https://openalex.org/W2161474341","https://openalex.org/W4302615923","https://openalex.org/W3203142394","https://openalex.org/W2351061015","https://openalex.org/W4220731478","https://openalex.org/W4242191701","https://openalex.org/W2108101990","https://openalex.org/W2361043785","https://openalex.org/W2365030987","https://openalex.org/W2573964224"],"abstract_inverted_index":{"The":[0],"output":[1,16,23,93],"coding":[2,24,94],"for":[3],"multiclass":[4],"learning":[5],"problems":[6],"is":[7,97],"a":[8,71,80,90,118,132],"generalization":[9],"of":[10,22,40,56,63,79,101,109],"one-per-class,":[11],"all-pairs,":[12],"and":[13,32,60,103,121],"error":[14,27],"correcting":[15,28],"codes.":[17],"Although,":[18],"the":[19,30,41,54,61,77,98,107,110],"prevailing":[20],"concepts":[21],"have":[25],"been":[26],"properties,":[29],"one-per-class":[31,102],"all-pairs":[33],"are":[34,48],"still":[35],"considered":[36],"to":[37,50,76],"be":[38],"one":[39],"state-of-art":[42],"methods.":[43],"However,":[44],"these":[45],"two":[46],"methods":[47],"contrary":[49],"each":[51],"other":[52],"in":[53],"aspect":[55],"producing":[57],"complex":[58],"dichotomies":[59],"problem":[62,120],"nonsense":[64],"outputs.":[65],"In":[66,85],"additions,":[67],"they":[68],"all":[69],"perform":[70],"prior":[72],"decomposition":[73],"without":[74],"regards":[75],"properties":[78,108],"given":[81],"training":[82],"data":[83],"set.":[84],"this":[86],"paper,":[87],"we":[88,125],"propose":[89],"new":[91],"data-driven":[92],"method":[95,130],"that":[96,127],"generalized":[99],"form":[100],"all-pairs.":[104],"We":[105],"present":[106,126],"proposed":[111,129],"method.":[112],"From":[113],"experimental":[114],"results":[115],"on":[116],"both":[117],"toy":[119],"real":[122],"benchmark":[123],"datasets,":[124],"our":[128],"achieves":[131],"comparable":[133],"performance":[134],"with":[135],"good":[136],"properties.":[137]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
