{"id":"https://openalex.org/W7164588740","doi":"https://doi.org/10.48550/arxiv.2606.13576","title":"Learning with Simulators: No Regret in a Computationally Bounded World","display_name":"Learning with Simulators: No Regret in a Computationally Bounded World","publication_year":2026,"publication_date":"2026-06-11","ids":{"openalex":"https://openalex.org/W7164588740","doi":"https://doi.org/10.48550/arxiv.2606.13576"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.13576","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.13576","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2606.13576","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5045715979","display_name":"Sasha Voitovych","orcid":"https://orcid.org/0000-0003-1840-476X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Voitovych, Sasha","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138519559","display_name":"Abhishek Shetty","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shetty, Abhishek","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089252105","display_name":"Noah Golowich","orcid":"https://orcid.org/0000-0003-2274-7861"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Golowich, Noah","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5138521559","display_name":"Alexander Rakhlin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rakhlin, Alexander","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12072","display_name":"Machine Learning and Algorithms","score":0.6592000126838684,"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":0.6592000126838684,"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/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.2531999945640564,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.043299999088048935,"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/bounded-function","display_name":"Bounded function","score":0.7228999733924866},{"id":"https://openalex.org/keywords/regret","display_name":"Regret","score":0.6345000267028809},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.5600000023841858},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.47850000858306885},{"id":"https://openalex.org/keywords/independence","display_name":"Independence (probability theory)","score":0.42660000920295715},{"id":"https://openalex.org/keywords/conditional-independence","display_name":"Conditional independence","score":0.3903999924659729},{"id":"https://openalex.org/keywords/proxy","display_name":"Proxy (statistics)","score":0.3546000123023987},{"id":"https://openalex.org/keywords/probably-approximately-correct-learning","display_name":"Probably approximately correct learning","score":0.3433000147342682},{"id":"https://openalex.org/keywords/polynomial","display_name":"Polynomial","score":0.32670000195503235}],"concepts":[{"id":"https://openalex.org/C34388435","wikidata":"https://www.wikidata.org/wiki/Q2267362","display_name":"Bounded function","level":2,"score":0.7228999733924866},{"id":"https://openalex.org/C50817715","wikidata":"https://www.wikidata.org/wiki/Q79895177","display_name":"Regret","level":2,"score":0.6345000267028809},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.5600000023841858},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4812999963760376},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.47850000858306885},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.46540001034736633},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.46140000224113464},{"id":"https://openalex.org/C35651441","wikidata":"https://www.wikidata.org/wiki/Q625303","display_name":"Independence (probability theory)","level":2,"score":0.42660000920295715},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.4009999930858612},{"id":"https://openalex.org/C79772020","wikidata":"https://www.wikidata.org/wiki/Q5159264","display_name":"Conditional independence","level":2,"score":0.3903999924659729},{"id":"https://openalex.org/C2780148112","wikidata":"https://www.wikidata.org/wiki/Q1432581","display_name":"Proxy (statistics)","level":2,"score":0.3546000123023987},{"id":"https://openalex.org/C176248197","wikidata":"https://www.wikidata.org/wiki/Q458526","display_name":"Probably approximately correct learning","level":4,"score":0.3433000147342682},{"id":"https://openalex.org/C90119067","wikidata":"https://www.wikidata.org/wiki/Q43260","display_name":"Polynomial","level":2,"score":0.32670000195503235},{"id":"https://openalex.org/C311688","wikidata":"https://www.wikidata.org/wiki/Q2393193","display_name":"Time complexity","level":2,"score":0.325300008058548},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3176000118255615},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.30489999055862427},{"id":"https://openalex.org/C2778445095","wikidata":"https://www.wikidata.org/wiki/Q18354077","display_name":"Sample complexity","level":2,"score":0.2971000075340271},{"id":"https://openalex.org/C43555835","wikidata":"https://www.wikidata.org/wiki/Q2300258","display_name":"Conditional probability distribution","level":2,"score":0.2939999997615814},{"id":"https://openalex.org/C149441793","wikidata":"https://www.wikidata.org/wiki/Q200726","display_name":"Probability distribution","level":2,"score":0.2921999990940094},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.2897000014781952},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.28940001130104065},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2888999879360199},{"id":"https://openalex.org/C110121322","wikidata":"https://www.wikidata.org/wiki/Q865811","display_name":"Distribution (mathematics)","level":2,"score":0.2856000065803528},{"id":"https://openalex.org/C203313322","wikidata":"https://www.wikidata.org/wiki/Q5158394","display_name":"Concept class","level":2,"score":0.2851000130176544},{"id":"https://openalex.org/C2779014939","wikidata":"https://www.wikidata.org/wiki/Q6510239","display_name":"Learning with errors","level":3,"score":0.28110000491142273},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.2793000042438507},{"id":"https://openalex.org/C2779915298","wikidata":"https://www.wikidata.org/wiki/Q7604400","display_name":"Statistical learning theory","level":3,"score":0.26649999618530273},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.26190000772476196},{"id":"https://openalex.org/C2982736386","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Statistical learning","level":2,"score":0.26080000400543213}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.13576","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.13576","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2606.13576","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.13576","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Understanding":[0],"the":[1,8,26,45,51,60,63,87,93,105,115,160,165,174],"minimal":[2],"assumptions":[3],"necessary":[4],"for":[5,31],"generalization":[6],"is":[7],"fundamental":[9],"question":[10],"in":[11,92,127,152],"learning":[12,89],"theory.":[13],"Unfortunately,":[14],"most":[15],"results":[16,30],"rely":[17],"heavily":[18],"on":[19,104],"independence":[20],"(or":[21],"some":[22],"proxy":[23],"thereof)":[24],"of":[25,47,117,133,164,173],"data-generating":[27],"process,":[28],"while":[29],"strongly":[32],"dependent":[33,72],"data":[34,64],"are":[35],"far":[36],"more":[37],"limited.":[38],"Towards":[39],"addressing":[40],"this":[41,111,128],"gap,":[42],"we":[43,81,84,109,136],"introduce":[44],"framework":[46,112],"simulatable":[48],"processes,":[49],"where":[50],"learner":[52],"has":[53],"access":[54,76],"to":[55,77,113],"a":[56,79,131,138,169],"simulator":[57],"that":[58,83,102,141],"approximates":[59],"distribution":[61],"generating":[62],"(which":[65],"may":[66],"be":[67],"an":[68],"arbitrarily":[69],"complex":[70],"and":[71,120,124],"process).":[73],"Surprisingly,":[74],"given":[75,145],"such":[78],"simulator,":[80],"show":[82,121],"can":[85],"recover":[86],"same":[88],"guarantees":[90],"as":[91],"classical":[94,175],"setting":[95],"with":[96,156],"independent":[97],"data,":[98],"namely,":[99],"error":[100],"bounds":[101],"depend":[103],"VC":[106,146],"dimension.":[107],"Further,":[108],"use":[110],"study":[114],"power":[116],"conditional":[118],"sampling":[119],"strict":[122],"statistical":[123],"computational":[125],"advantages":[126],"setting.":[129],"As":[130],"highlight":[132],"our":[134],"framework,":[135],"exhibit":[137],"single":[139],"algorithm":[140],"simultaneously":[142],"learns":[143],"any":[144],"class":[147],"under":[148],"all":[149],"processes":[150],"samplable":[151],"bounded":[153],"polynomial":[154],"time,":[155],"regret":[157],"controlled":[158],"by":[159],"time-bounded":[161],"Kolmogorov":[162],"complexity":[163],"process.":[166],"This":[167],"provides":[168],"significant":[170],"conceptual":[171],"broadening":[172],"PAC":[176],"model.":[177]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-06-13T00:00:00"}