{"id":"https://openalex.org/W2016133707","doi":"https://doi.org/10.1145/1143844.1143970","title":"Totally corrective boosting algorithms that maximize the margin","display_name":"Totally corrective boosting algorithms that maximize the margin","publication_year":2006,"publication_date":"2006-01-01","ids":{"openalex":"https://openalex.org/W2016133707","doi":"https://doi.org/10.1145/1143844.1143970","mag":"2016133707"},"language":"en","primary_location":{"id":"doi:10.1145/1143844.1143970","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1143844.1143970","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 23rd international conference on Machine learning  - ICML '06","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/A5108549518","display_name":"Manfred K. Warmuth","orcid":null},"institutions":[{"id":"https://openalex.org/I185103710","display_name":"University of California, Santa Cruz","ror":"https://ror.org/03s65by71","country_code":"US","type":"education","lineage":["https://openalex.org/I185103710"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Manfred K. Warmuth","raw_affiliation_strings":["University of California at Santa Cruz, Santa Cruz, CA","University of California at Santa Cruz, Santa Cruz, CA#TAB#"],"affiliations":[{"raw_affiliation_string":"University of California at Santa Cruz, Santa Cruz, CA","institution_ids":["https://openalex.org/I185103710"]},{"raw_affiliation_string":"University of California at Santa Cruz, Santa Cruz, CA#TAB#","institution_ids":["https://openalex.org/I185103710"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082590468","display_name":"Jun Liao","orcid":"https://orcid.org/0000-0003-0617-5840"},"institutions":[{"id":"https://openalex.org/I185103710","display_name":"University of California, Santa Cruz","ror":"https://ror.org/03s65by71","country_code":"US","type":"education","lineage":["https://openalex.org/I185103710"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jun Liao","raw_affiliation_strings":["University of California at Santa Cruz, Santa Cruz, CA","University of California at Santa Cruz, Santa Cruz, CA#TAB#"],"affiliations":[{"raw_affiliation_string":"University of California at Santa Cruz, Santa Cruz, CA","institution_ids":["https://openalex.org/I185103710"]},{"raw_affiliation_string":"University of California at Santa Cruz, Santa Cruz, CA#TAB#","institution_ids":["https://openalex.org/I185103710"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5035416263","display_name":"Gunnar R\u00e4tsch","orcid":"https://orcid.org/0000-0001-5486-8532"},"institutions":[{"id":"https://openalex.org/I149899117","display_name":"Max Planck Society","ror":"https://ror.org/01hhn8329","country_code":"DE","type":"funder","lineage":["https://openalex.org/I149899117"]},{"id":"https://openalex.org/I4210147862","display_name":"Friedrich Miescher Laboratory","ror":"https://ror.org/04vh1tq58","country_code":"DE","type":"nonprofit","lineage":["https://openalex.org/I149899117","https://openalex.org/I4210147862"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Gunnar R\u00e4tsch","raw_affiliation_strings":["Friedrich Miescher Laboratory of the Max Planck Society, T\u00fcbingen, Germany and Boosting, Margins, Convergence, Relative Entropy, Bregman Divergences, Bregman Projection","Friedrich Miescher Laboratory of the Max Planck Society, T\u00fcbingen, Germany and Boosting, Margins, Convergence, Relative Entropy, Bregman Divergences, Bregman Projection#TAB#"],"affiliations":[{"raw_affiliation_string":"Friedrich Miescher Laboratory of the Max Planck Society, T\u00fcbingen, Germany and Boosting, Margins, Convergence, Relative Entropy, Bregman Divergences, Bregman Projection","institution_ids":["https://openalex.org/I4210147862"]},{"raw_affiliation_string":"Friedrich Miescher Laboratory of the Max Planck Society, T\u00fcbingen, Germany and Boosting, Margins, Convergence, Relative Entropy, Bregman Divergences, Bregman Projection#TAB#","institution_ids":["https://openalex.org/I4210147862","https://openalex.org/I149899117"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5108549518"],"corresponding_institution_ids":["https://openalex.org/I185103710"],"apc_list":null,"apc_paid":null,"fwci":9.7694,"has_fulltext":false,"cited_by_count":121,"citation_normalized_percentile":{"value":0.97919242,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1001","last_page":"1008"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12072","display_name":"Machine Learning and Algorithms","score":0.9998999834060669,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.9998999834060669,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9991000294685364,"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9987999796867371,"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/boosting","display_name":"Boosting (machine learning)","score":0.8905442953109741},{"id":"https://openalex.org/keywords/adaboost","display_name":"AdaBoost","score":0.6147394180297852},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5346616506576538},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.46446293592453003},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.4633197486400604},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.4519864320755005},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4453226923942566},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.4162466526031494},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.28239041566848755},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.23075109720230103},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.16654935479164124}],"concepts":[{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.8905442953109741},{"id":"https://openalex.org/C141404830","wikidata":"https://www.wikidata.org/wiki/Q2823869","display_name":"AdaBoost","level":3,"score":0.6147394180297852},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5346616506576538},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.46446293592453003},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.4633197486400604},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.4519864320755005},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4453226923942566},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.4162466526031494},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.28239041566848755},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.23075109720230103},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.16654935479164124},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1145/1143844.1143970","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1143844.1143970","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 23rd international conference on Machine learning  - ICML '06","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.144.8195","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.144.8195","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cse.ucsc.edu/~manfred/pubs/C75.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.77.5353","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.77.5353","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://imls.engr.oregonstate.edu/www/htdocs/proceedings/icml2006/126_Totally_Corrective_B.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W16591383","https://openalex.org/W1540007258","https://openalex.org/W1899157803","https://openalex.org/W1918179283","https://openalex.org/W1975846642","https://openalex.org/W1983739894","https://openalex.org/W1985949731","https://openalex.org/W1988790447","https://openalex.org/W2011395874","https://openalex.org/W2024046085","https://openalex.org/W2032210760","https://openalex.org/W2033468335","https://openalex.org/W2075567596","https://openalex.org/W2098300287","https://openalex.org/W2099968818","https://openalex.org/W2129113961","https://openalex.org/W2132044913","https://openalex.org/W2172195373","https://openalex.org/W3029645440","https://openalex.org/W4285719527"],"related_works":["https://openalex.org/W2327035729","https://openalex.org/W2348748958","https://openalex.org/W3039673966","https://openalex.org/W1538046993","https://openalex.org/W2884325279","https://openalex.org/W1570592793","https://openalex.org/W1525436954","https://openalex.org/W2385662756","https://openalex.org/W2585372724","https://openalex.org/W2241444561"],"abstract_inverted_index":{"We":[0,26],"consider":[1],"boosting":[2,72,149],"algorithms":[3,109,120],"that":[4],"maintain":[5],"a":[6,9,16,146],"distribution":[7,23,52],"over":[8],"set":[10],"of":[11,45,81,134],"examples.":[12],"At":[13],"each":[14],"iteration":[15,103,159],"weak":[17,135],"hypothesis":[18,48],"is":[19,24,64,74,94,157],"received":[20],"and":[21,141],"the":[22,32,43,46,50,67,79,101,106,119,123,126,138],"updated.":[25],"motivate":[27],"these":[28],"updates":[29],"as":[30,110],"minimizing":[31],"relative":[33],"entropy":[34],"subject":[35],"to":[36,53,75,87],"linear":[37],"constraints.":[38],"For":[39],"example":[40],"AdaBoost":[41,63],"constrains":[42],"edge":[44],"last":[47,68],"w.r.t.":[49,66],"updated":[51],"be":[54,76,88],"at":[55,89],"most":[56,90],"\u03b3":[57,93],"=":[58],"0.":[59],"In":[60],"some":[61],"sense,":[62],"\"corrective\"":[65],"hypothesis.":[69],"A":[70],"cleaner":[71],"method":[73],"\"totally":[77],"corrective\":":[78],"edges":[80],"all":[82],"past":[83],"hypotheses":[84,136],"are":[85,142],"constrained":[86],"\u03b3,":[91,118],"where":[92],"suitably":[95],"adapted.Using":[96],"new":[97],"techniques,":[98],"we":[99],"prove":[100],"same":[102],"bounds":[104],"for":[105,111,154],"totally":[107,127,147],"corrective":[108,113,128,139,148],"their":[112],"versions.":[114],"Moreover":[115],"with":[116,144,151],"adaptive":[117],"provably":[121],"maximizes":[122],"margin.":[124],"Experimentally,":[125],"versions":[129],"return":[130],"smaller":[131],"convex":[132],"combinations":[133],"than":[137],"ones":[140],"competitive":[143],"LPBoost,":[145],"algorithm":[150],"no":[152,158],"regularization,":[153],"which":[155],"there":[156],"bound":[160],"known.":[161]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":7},{"year":2020,"cited_by_count":10},{"year":2019,"cited_by_count":6},{"year":2018,"cited_by_count":7},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":4},{"year":2015,"cited_by_count":7},{"year":2014,"cited_by_count":5},{"year":2013,"cited_by_count":9},{"year":2012,"cited_by_count":5}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}
