{"id":"https://openalex.org/W2274227197","doi":"https://doi.org/10.48550/arxiv.1403.3465","title":"A Survey of Algorithms and Analysis for Adaptive Online Learning","display_name":"A Survey of Algorithms and Analysis for Adaptive Online Learning","publication_year":2014,"publication_date":"2014-03-14","ids":{"openalex":"https://openalex.org/W2274227197","doi":"https://doi.org/10.48550/arxiv.1403.3465","mag":"2274227197"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:1403.3465","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/1403.3465","pdf_url":"https://arxiv.org/pdf/1403.3465","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,"listed_in":[],"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":null,"raw_type":"text"},"volume":null,"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1403.3465","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5040311844","display_name":"H. Brendan McMahan","orcid":"https://orcid.org/0009-0003-5892-4193","observed_orcids":["https://orcid.org/0009-0003-5892-4193"]},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"McMahan, H. Brendan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":["https://openalex.org/A5040311844"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":27,"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/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.9253000020980835,"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"}},"topics":[{"id":"https://openalex.org/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.9253000020980835,"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":0.06710000336170197,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.0010999999940395355,"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/adaptive-e-learning","display_name":"adaptive e-learning","score":0.7850000262260437},{"id":"https://openalex.org/keywords/follow-the-regularized-leader","display_name":"follow-the-regularized-leader","score":0.8960000276565552},{"id":"https://openalex.org/keywords/dual-averaging","display_name":"dual averaging","score":0.9739999771118164},{"id":"https://openalex.org/keywords/mirror-descent","display_name":"mirror descent","score":0.9980000257492065},{"id":"https://openalex.org/keywords/regret-bounds","display_name":"regret bounds","score":0.8820000290870667},{"id":"https://openalex.org/keywords/time-varying-weights","display_name":"time-varying weights","score":0.7300000190734863},{"id":"https://openalex.org/keywords/online-gradient-descent","display_name":"online gradient descent","score":0.6069999933242798},{"id":"https://openalex.org/keywords/adagrad","display_name":"AdaGrad","score":0.7020000219345093},{"id":"https://openalex.org/keywords/primal-dual-analysis","display_name":"primal-dual analysis","score":0.6370000243186951},{"id":"https://openalex.org/keywords/potential-function","display_name":"potential function","score":0.6290000081062317}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5888801217079163},{"id":"https://openalex.org/C2986087404","wikidata":"https://www.wikidata.org/wiki/Q15946010","display_name":"Online learning","level":2,"score":0.47459977865219116},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.40201425552368164},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.38527733087539673},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3698677122592926},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.35545629262924194},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.1679862141609192}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:1403.3465","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/1403.3465","pdf_url":"https://arxiv.org/pdf/1403.3465","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,"listed_in":[],"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":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.1403.3465","doi":"https://doi.org/10.48550/arxiv.1403.3465","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1403.3465","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,"listed_in":[],"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"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1403.3465","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/1403.3465","pdf_url":"https://arxiv.org/pdf/1403.3465","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,"listed_in":[],"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":null,"raw_type":"text"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W1518461880","https://openalex.org/W1594567720","https://openalex.org/W1788809966","https://openalex.org/W1964009380","https://openalex.org/W1988790447","https://openalex.org/W2016384870","https://openalex.org/W2069317438","https://openalex.org/W2074586650","https://openalex.org/W2074694452","https://openalex.org/W2077008409","https://openalex.org/W2077723394","https://openalex.org/W2093825590","https://openalex.org/W2096199223","https://openalex.org/W2096646162","https://openalex.org/W2097931325","https://openalex.org/W2109339818","https://openalex.org/W2109775151","https://openalex.org/W2116606500","https://openalex.org/W2118075434","https://openalex.org/W2129160848","https://openalex.org/W2139338362","https://openalex.org/W2139759436","https://openalex.org/W2145630740","https://openalex.org/W2146482778","https://openalex.org/W2146502635","https://openalex.org/W2148825261","https://openalex.org/W2157998899","https://openalex.org/W2169713291","https://openalex.org/W2274356684","https://openalex.org/W2296319761","https://openalex.org/W2611627047","https://openalex.org/W2952004949"],"related_works":["https://openalex.org/W2903829737","https://openalex.org/W1850731992","https://openalex.org/W7100271330","https://openalex.org/W2752776705","https://openalex.org/W2985478892","https://openalex.org/W90718569","https://openalex.org/W2224490792","https://openalex.org/W4379255804","https://openalex.org/W7214242046","https://openalex.org/W4391621389"],"abstract_inverted_index":{"We":[0,64],"present":[1,65],"tools":[2],"for":[3,47,182],"the":[4,16,29,86,146,153,167,177],"analysis":[5,83,99,165],"of":[6,71,166],"Follow-The-Regularized-Leader":[7],"(FTRL),":[8],"Dual":[9,156],"Averaging,":[10],"and":[11,44,81,120,130,158,185],"Mirror":[12,127,142,159],"Descent":[13,58,128,143,160],"algorithms":[14,54,161],"when":[15],"regularizer":[17],"(equivalently,":[18],"prox-function":[19],"or":[20,112],"learning":[21,62],"rate":[22],"schedule)":[23],"is":[24],"chosen":[25],"adaptively":[26],"based":[27],"on":[28,41],"data.":[30],"Adaptivity":[31],"can":[32],"be":[33],"used":[34],"to":[35,101,139,151],"prove":[36,117],"regret":[37,49,172],"bounds":[38,50,103,173],"that":[39,84],"hold":[40],"every":[42],"round,":[43],"also":[45],"allows":[46,137],"data-dependent":[48],"as":[51,104,106],"in":[52,74,89,145,163,176],"AdaGrad-style":[53],"(e.g.,":[55],"Online":[56],"Gradient":[57],"with":[59,188],"adaptive":[60,126],"per-coordinate":[61],"rates).":[63],"results":[66],"from":[67],"a":[68,75,79,118,131],"large":[69],"number":[70],"prior":[72],"works":[73],"unified":[76],"manner,":[77],"using":[78],"modular":[80],"tight":[82,105],"isolates":[85],"key":[87,150],"arguments":[88],"easily":[90],"re-usable":[91],"lemmas.":[92],"This":[93],"approach":[94],"strengthens":[95],"pre-viously":[96],"known":[97],"FTRL":[98,134],"techniques":[100],"produce":[102],"those":[107],"achieved":[108],"by":[109],"potential":[110],"functions":[111],"primal-dual":[113],"analysis.":[114],"Further,":[115],"we":[116],"general":[119,179],"exact":[121],"equivalence":[122],"between":[123,155],"an":[124,164],"arbitrary":[125,183],"algorithm":[129,144,169],"correspond-":[132],"ing":[133],"update,":[135],"which":[136],"us":[138],"analyze":[140],"any":[141],"same":[147],"framework.":[148],"The":[149],"bridging":[152],"gap":[154],"Averaging":[157],"lies":[162],"FTRL-Proximal":[168],"family.":[170],"Our":[171],"are":[174],"proved":[175],"most":[178],"form,":[180],"holding":[181],"norms":[184],"non-smooth":[186],"regularizers":[187],"time-varying":[189],"weight.":[190]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":6},{"year":2016,"cited_by_count":3},{"year":2015,"cited_by_count":1}],"updated_date":"2026-11-03T10:50:19.383937","created_date":"2016-06-24T00:00:00"}