{"id":"https://openalex.org/W3101300262","doi":"https://doi.org/10.1145/3406325.3451087","title":"A theory of universal learning","display_name":"A theory of universal learning","publication_year":2021,"publication_date":"2021-06-15","ids":{"openalex":"https://openalex.org/W3101300262","doi":"https://doi.org/10.1145/3406325.3451087","mag":"3101300262"},"language":"en","primary_location":{"id":"doi:10.1145/3406325.3451087","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3406325.3451087","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3406325.3451087","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 53rd Annual ACM SIGACT Symposium on Theory of Computing","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3406325.3451087","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5014847122","display_name":"Olivier Bousquet","orcid":"https://orcid.org/0000-0002-2567-2079"},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]},{"id":"https://openalex.org/I4210100430","display_name":"Google (Switzerland)","ror":"https://ror.org/014f9c269","country_code":"CH","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210100430","https://openalex.org/I4210128969"]}],"countries":["CH","US"],"is_corresponding":true,"raw_author_name":"Olivier Bousquet","raw_affiliation_strings":["Google, Switzerland","Google,,,,,"],"affiliations":[{"raw_affiliation_string":"Google, Switzerland","institution_ids":["https://openalex.org/I4210100430"]},{"raw_affiliation_string":"Google,,,,,","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074158209","display_name":"Steve Hanneke","orcid":null},"institutions":[{"id":"https://openalex.org/I160992636","display_name":"Toyota Technological Institute at Chicago","ror":"https://ror.org/02sn5gb64","country_code":"US","type":"education","lineage":["https://openalex.org/I160992636"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Steve Hanneke","raw_affiliation_strings":["Toyota Technological Institute at Chicago, USA","[Toyota Technological Institute at Chicago, USA]"],"affiliations":[{"raw_affiliation_string":"Toyota Technological Institute at Chicago, USA","institution_ids":["https://openalex.org/I160992636"]},{"raw_affiliation_string":"[Toyota Technological Institute at Chicago, USA]","institution_ids":["https://openalex.org/I160992636"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047793114","display_name":"Shay Moran","orcid":"https://orcid.org/0000-0002-8662-2737"},"institutions":[{"id":"https://openalex.org/I174306211","display_name":"Technion \u2013 Israel Institute of Technology","ror":"https://ror.org/03qryx823","country_code":"IL","type":"education","lineage":["https://openalex.org/I174306211"]},{"id":"https://openalex.org/I4210117425","display_name":"Google (Israel)","ror":"https://ror.org/02c20ys54","country_code":"IL","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210117425","https://openalex.org/I4210128969"]}],"countries":["IL"],"is_corresponding":false,"raw_author_name":"Shay Moran","raw_affiliation_strings":["Technion, Israel / Google Research, Israel","Technion-Israel Institute of Technology"],"affiliations":[{"raw_affiliation_string":"Technion, Israel / Google Research, Israel","institution_ids":["https://openalex.org/I4210117425"]},{"raw_affiliation_string":"Technion-Israel Institute of Technology","institution_ids":["https://openalex.org/I174306211"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063843509","display_name":"Ramon van Handel","orcid":"https://orcid.org/0000-0003-4026-8100"},"institutions":[{"id":"https://openalex.org/I20089843","display_name":"Princeton University","ror":"https://ror.org/00hx57361","country_code":"US","type":"education","lineage":["https://openalex.org/I20089843"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ramon van Handel","raw_affiliation_strings":["Princeton University, USA","Princeton University"],"affiliations":[{"raw_affiliation_string":"Princeton University, USA","institution_ids":["https://openalex.org/I20089843"]},{"raw_affiliation_string":"Princeton University","institution_ids":["https://openalex.org/I20089843"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5041051779","display_name":"Amir Yehudayoff","orcid":"https://orcid.org/0000-0002-0177-1814"},"institutions":[{"id":"https://openalex.org/I174306211","display_name":"Technion \u2013 Israel Institute of Technology","ror":"https://ror.org/03qryx823","country_code":"IL","type":"education","lineage":["https://openalex.org/I174306211"]}],"countries":["IL"],"is_corresponding":false,"raw_author_name":"Amir Yehudayoff","raw_affiliation_strings":["Technion, Israel","Technion/Israel"],"affiliations":[{"raw_affiliation_string":"Technion, Israel","institution_ids":["https://openalex.org/I174306211"]},{"raw_affiliation_string":"Technion/Israel","institution_ids":["https://openalex.org/I174306211"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5014847122"],"corresponding_institution_ids":["https://openalex.org/I1291425158","https://openalex.org/I4210100430"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.00936246,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"532","last_page":"541"},"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/T11269","display_name":"Algorithms and Data Compression","score":0.9966999888420105,"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":0.9951000213623047,"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/learnability","display_name":"Learnability","score":0.8883194923400879},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.631103515625},{"id":"https://openalex.org/keywords/probably-approximately-correct-learning","display_name":"Probably approximately correct learning","score":0.6142968535423279},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.4816809594631195},{"id":"https://openalex.org/keywords/exponential-function","display_name":"Exponential function","score":0.46835842728614807},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.45381730794906616},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.44763362407684326},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.43179476261138916},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.40631526708602905},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.38229772448539734},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.35350602865219116},{"id":"https://openalex.org/keywords/computational-learning-theory","display_name":"Computational learning theory","score":0.27884215116500854},{"id":"https://openalex.org/keywords/active-learning","display_name":"Active learning (machine learning)","score":0.21083292365074158},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.11653289198875427}],"concepts":[{"id":"https://openalex.org/C2777723229","wikidata":"https://www.wikidata.org/wiki/Q4367921","display_name":"Learnability","level":2,"score":0.8883194923400879},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.631103515625},{"id":"https://openalex.org/C176248197","wikidata":"https://www.wikidata.org/wiki/Q458526","display_name":"Probably approximately correct learning","level":4,"score":0.6142968535423279},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.4816809594631195},{"id":"https://openalex.org/C151376022","wikidata":"https://www.wikidata.org/wiki/Q168698","display_name":"Exponential function","level":2,"score":0.46835842728614807},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.45381730794906616},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44763362407684326},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.43179476261138916},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.40631526708602905},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.38229772448539734},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.35350602865219116},{"id":"https://openalex.org/C50292564","wikidata":"https://www.wikidata.org/wiki/Q2462783","display_name":"Computational learning theory","level":3,"score":0.27884215116500854},{"id":"https://openalex.org/C77967617","wikidata":"https://www.wikidata.org/wiki/Q4677561","display_name":"Active learning (machine learning)","level":2,"score":0.21083292365074158},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.11653289198875427},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1145/3406325.3451087","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3406325.3451087","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3406325.3451087","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 53rd Annual ACM SIGACT Symposium on Theory of Computing","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2011.04483","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2011.04483","pdf_url":"https://arxiv.org/pdf/2011.04483","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"mag:3101300262","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/2011.04483.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.2011.04483","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2011.04483","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.1145/3406325.3451087","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3406325.3451087","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3406325.3451087","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 53rd Annual ACM SIGACT Symposium on Theory of Computing","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.5099999904632568,"display_name":"Quality Education"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320322252","display_name":"Israel Science Foundation","ror":"https://ror.org/04sazxf24"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3101300262.pdf","grobid_xml":"https://content.openalex.org/works/W3101300262.grobid-xml"},"referenced_works_count":31,"referenced_works":["https://openalex.org/W22319034","https://openalex.org/W146740654","https://openalex.org/W1529878936","https://openalex.org/W1564947197","https://openalex.org/W1807800941","https://openalex.org/W1978923178","https://openalex.org/W1996437515","https://openalex.org/W1996760744","https://openalex.org/W2016257995","https://openalex.org/W2019363670","https://openalex.org/W2029538739","https://openalex.org/W2029604420","https://openalex.org/W2045313701","https://openalex.org/W2059507684","https://openalex.org/W2066688546","https://openalex.org/W2118768417","https://openalex.org/W2125610282","https://openalex.org/W2129113961","https://openalex.org/W2154952480","https://openalex.org/W2165701400","https://openalex.org/W2623739609","https://openalex.org/W2771281976","https://openalex.org/W2913378067","https://openalex.org/W2953367795","https://openalex.org/W2963944825","https://openalex.org/W3017128687","https://openalex.org/W3095697731","https://openalex.org/W3099192805","https://openalex.org/W3139996414","https://openalex.org/W4238284510","https://openalex.org/W4238893454"],"related_works":["https://openalex.org/W3168797133","https://openalex.org/W2005530305","https://openalex.org/W2046995465","https://openalex.org/W2201177080","https://openalex.org/W2186076924","https://openalex.org/W1555424171","https://openalex.org/W43111499","https://openalex.org/W2950504128","https://openalex.org/W2162542068","https://openalex.org/W3007266553","https://openalex.org/W2025967375","https://openalex.org/W2069401480","https://openalex.org/W1965006329","https://openalex.org/W2904118847","https://openalex.org/W2015481793","https://openalex.org/W2155831576","https://openalex.org/W3213890428","https://openalex.org/W1970472910","https://openalex.org/W2107656646","https://openalex.org/W811226091"],"abstract_inverted_index":{"How":[0],"quickly":[1],"can":[2,76],"a":[3,20,39,156,205],"given":[4,109,227],"class":[5,229],"of":[6,19,34,41,44,58,67,74,82,97,118,124,148,159,165,175,184,201,214,225,242],"concepts":[7],"be":[8],"learned":[9],"from":[10],"examples?":[11],"It":[12],"is":[13,104,204,245],"common":[14],"to":[15,155,180,283,285],"measure":[16],"the":[17,32,35,42,48,55,65,70,79,83,95,101,112,116,122,160,163,166,173,182,196,222,260,275],"performance":[18,183],"supervised":[21],"machine":[22,98,149],"learning":[23,68,75,84,140,185,223,256,288],"algorithm":[24],"by":[25,248],"plotting":[26],"its":[27],"\"learning":[28],"curve\",":[29],"that":[30,142,221,258],"is,":[31],"decay":[33,230],"error":[36],"rate":[37,263],"as":[38,127],"function":[40],"number":[43,117],"training":[45,119],"examples.":[46],"However,":[47],"classical":[49],"theoretical":[50],"framework":[51],"for":[52],"understanding":[53],"learnability,":[54],"PAC":[56,72,167],"model":[57,73,141],"Vapnik-Chervonenkis":[59],"and":[60,130,252],"Valiant,":[61],"does":[62,92],"not":[63,93],"explain":[64],"behavior":[66],"curves:":[69],"distribution-free":[71],"only":[77,210,274],"bound":[78],"upper":[80],"envelope":[81],"curves":[85,224],"over":[86,195],"all":[87],"possible":[88,212,262],"data":[89,102,189],"distributions.":[90],"This":[91],"match":[94],"practice":[96],"learning,":[99,150,177],"where":[100],"source":[103],"typically":[105],"fixed":[106],"in":[107,162,264,271],"any":[108,226],"scenario,":[110],"while":[111],"learner":[113],"may":[114],"choose":[115],"examples":[120],"on":[121,187],"basis":[123],"factors":[125],"such":[126,145],"computational":[128],"resources":[129],"desired":[131],"accuracy.":[132],"In":[133],"this":[134,202,272],"paper,":[135],"we":[136,171,219,253,269],"study":[137],"an":[138,233],"alternative":[139],"better":[143],"captures":[144],"practical":[146],"aspects":[147],"but":[151,191],"still":[152],"gives":[153],"rise":[154],"complete":[157],"theory":[158],"learnable":[161],"spirit":[164],"model.":[168],"More":[169,217],"precisely,":[170,218],"consider":[172,270],"problem":[174],"universal":[176,215],"which":[178],"aims":[179],"understand":[181],"algorithms":[186,257],"every":[188],"distribution,":[190],"without":[192],"requiring":[193],"uniformity":[194],"distribution.":[197],"The":[198],"main":[199],"result":[200],"paper":[203,273],"remarkable":[206],"trichotomy:":[207],"there":[208],"are":[209,281],"three":[211],"rates":[213],"learning.":[216],"show":[220],"concept":[228],"either":[231],"at":[232],"exponential,":[234],"linear,":[235],"or":[236],"arbitrarily":[237],"slow":[238],"rates.":[239],"Moreover,":[240],"each":[241,265],"these":[243],"cases":[244],"completely":[246],"characterized":[247],"appropriate":[249],"combinatorial":[250],"parameters,":[251],"exhibit":[254],"optimal":[255],"achieve":[259],"best":[261],"case.":[266],"For":[267],"concreteness,":[268],"realizable":[276],"case,":[277],"though":[278],"analogous":[279],"results":[280],"expected":[282],"extend":[284],"more":[286],"general":[287],"scenarios.":[289]},"counts_by_year":[],"updated_date":"2026-02-09T09:26:11.010843","created_date":"2025-10-10T00:00:00"}
