{"id":"https://openalex.org/W3193777527","doi":"https://doi.org/10.1109/tnnls.2021.3105146","title":"Distributed Online Learning With Multiple Kernels","display_name":"Distributed Online Learning With Multiple Kernels","publication_year":2021,"publication_date":"2021-08-23","ids":{"openalex":"https://openalex.org/W3193777527","doi":"https://doi.org/10.1109/tnnls.2021.3105146","mag":"3193777527","pmid":"https://pubmed.ncbi.nlm.nih.gov/34424849"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2021.3105146","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2021.3105146","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5084652371","display_name":"Song\u2010Nam Hong","orcid":"https://orcid.org/0000-0002-9535-2521"},"institutions":[{"id":"https://openalex.org/I4575257","display_name":"Hanyang University","ror":"https://ror.org/046865y68","country_code":"KR","type":"education","lineage":["https://openalex.org/I4575257"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Songnam Hong","raw_affiliation_strings":["Department of Electronic Engineering, Hanyang University, Seoul, South Korea"],"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Hanyang University, Seoul, South Korea","institution_ids":["https://openalex.org/I4575257"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5001728130","display_name":"Jeongmin Chae","orcid":"https://orcid.org/0000-0001-6007-1300"},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jeongmin Chae","raw_affiliation_strings":["Department of Electrical Engineering, University of Southern California, Los Angeles, CA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, University of Southern California, Los Angeles, CA, USA","institution_ids":["https://openalex.org/I1174212"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5084652371"],"corresponding_institution_ids":["https://openalex.org/I4575257"],"apc_list":null,"apc_paid":null,"fwci":3.6675,"has_fulltext":false,"cited_by_count":32,"citation_normalized_percentile":{"value":0.93216071,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"34","issue":"3","first_page":"1263","last_page":"1277"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12879","display_name":"Distributed Sensor Networks and Detection Algorithms","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T12879","display_name":"Distributed Sensor Networks and Detection Algorithms","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9979000091552734,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.9975000023841858,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7187612056732178},{"id":"https://openalex.org/keywords/regret","display_name":"Regret","score":0.7078943848609924},{"id":"https://openalex.org/keywords/online-learning","display_name":"Online learning","score":0.6191117763519287},{"id":"https://openalex.org/keywords/sublinear-function","display_name":"Sublinear function","score":0.6063520908355713},{"id":"https://openalex.org/keywords/hindsight-bias","display_name":"Hindsight bias","score":0.5922707915306091},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.5168483853340149},{"id":"https://openalex.org/keywords/streaming-data","display_name":"Streaming data","score":0.45967724919319153},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.45937857031822205},{"id":"https://openalex.org/keywords/distributed-learning","display_name":"Distributed learning","score":0.4273000955581665},{"id":"https://openalex.org/keywords/function-approximation","display_name":"Function approximation","score":0.42563438415527344},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4200405478477478},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.40420955419540405},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.22615447640419006},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.2181955873966217},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16321662068367004}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7187612056732178},{"id":"https://openalex.org/C50817715","wikidata":"https://www.wikidata.org/wiki/Q79895177","display_name":"Regret","level":2,"score":0.7078943848609924},{"id":"https://openalex.org/C2986087404","wikidata":"https://www.wikidata.org/wiki/Q15946010","display_name":"Online learning","level":2,"score":0.6191117763519287},{"id":"https://openalex.org/C117160843","wikidata":"https://www.wikidata.org/wiki/Q338652","display_name":"Sublinear function","level":2,"score":0.6063520908355713},{"id":"https://openalex.org/C10347200","wikidata":"https://www.wikidata.org/wiki/Q1960297","display_name":"Hindsight bias","level":2,"score":0.5922707915306091},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.5168483853340149},{"id":"https://openalex.org/C2777611316","wikidata":"https://www.wikidata.org/wiki/Q39045282","display_name":"Streaming data","level":2,"score":0.45967724919319153},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.45937857031822205},{"id":"https://openalex.org/C2779582901","wikidata":"https://www.wikidata.org/wiki/Q21013010","display_name":"Distributed learning","level":2,"score":0.4273000955581665},{"id":"https://openalex.org/C91873725","wikidata":"https://www.wikidata.org/wiki/Q3445816","display_name":"Function approximation","level":3,"score":0.42563438415527344},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4200405478477478},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.40420955419540405},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.22615447640419006},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2181955873966217},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16321662068367004},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"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/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","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},{"id":"https://openalex.org/C19417346","wikidata":"https://www.wikidata.org/wiki/Q7922","display_name":"Pedagogy","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2021.3105146","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2021.3105146","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:34424849","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/34424849","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on neural networks and learning systems","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G393340904","display_name":null,"funder_award_id":"NRF-2020R1A2C1099836","funder_id":"https://openalex.org/F4320328359","funder_display_name":"Ministry of Science and ICT, South Korea"}],"funders":[{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"},{"id":"https://openalex.org/F4320328359","display_name":"Ministry of Science and ICT, South Korea","ror":"https://ror.org/01wpjm123"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W1510073064","https://openalex.org/W1560724230","https://openalex.org/W1986078872","https://openalex.org/W2029171653","https://openalex.org/W2040731319","https://openalex.org/W2058401212","https://openalex.org/W2109743529","https://openalex.org/W2139320579","https://openalex.org/W2144902422","https://openalex.org/W2150621701","https://openalex.org/W2154462399","https://openalex.org/W2164278908","https://openalex.org/W2169278871","https://openalex.org/W2210220586","https://openalex.org/W2247545798","https://openalex.org/W2517346953","https://openalex.org/W2566505556","https://openalex.org/W2594297742","https://openalex.org/W2599228073","https://openalex.org/W2778702574","https://openalex.org/W2785250477","https://openalex.org/W2789731659","https://openalex.org/W2883001236","https://openalex.org/W2900120080","https://openalex.org/W2912099989","https://openalex.org/W2963798770","https://openalex.org/W2963976431","https://openalex.org/W2989289980","https://openalex.org/W3011863222","https://openalex.org/W3021654819","https://openalex.org/W3143839440","https://openalex.org/W3193777527","https://openalex.org/W4205841652","https://openalex.org/W4249667877","https://openalex.org/W4298876635","https://openalex.org/W6681302627","https://openalex.org/W6683181193","https://openalex.org/W6688111153","https://openalex.org/W6748213982","https://openalex.org/W6755988804"],"related_works":["https://openalex.org/W3197854638","https://openalex.org/W3140454661","https://openalex.org/W4245029315","https://openalex.org/W1492315459","https://openalex.org/W1512434910","https://openalex.org/W2540910169","https://openalex.org/W3148904318","https://openalex.org/W4387846338","https://openalex.org/W4401164587","https://openalex.org/W4319773485"],"abstract_inverted_index":{"We":[0,87],"consider":[1],"the":[2,72,109,121,133,138,157,160],"problem":[3],"of":[4,12,74,80,159],"learning":[5,20,33,41,56],"a":[6,10,15,37,43,54,83,113,117],"nonlinear":[7],"function":[8,115,123],"over":[9,92],"network":[11,110],"learners":[13],"in":[14,108,124],"fully":[16,38,44],"decentralized":[17,45],"fashion.":[18],"Online":[19],"is":[21,35,62,68],"additionally":[22],"assumed,":[23],"where":[24],"every":[25,106],"learner":[26,107],"receives":[27],"continuous":[28],"streaming":[29],"data":[30,145],"locally.":[31],"This":[32],"model":[34],"called":[36],"distributed":[39,84],"online":[40,46,76,165],"(or":[42],"federated":[47],"learning).":[48],"For":[49],"this":[50],"model,":[51],"we":[52,155],"propose":[53],"novel":[55],"framework":[57],"with":[58,152],"multiple":[59],"kernels,":[60],"which":[61],"named":[63],"DOMKL.":[64],"The":[65],"proposed":[66,161],"DOMKL":[67,91,131,162],"devised":[69],"by":[70],"harnessing":[71],"principles":[73],"an":[75,98],"alternating":[77],"direction":[78],"method":[79],"multipliers":[81],"and":[82,167],"Hedge":[85],"algorithm.":[86],"theoretically":[88],"prove":[89],"that":[90,105,130],"T":[93],"time":[94],"slots":[95],"can":[96,111],"achieve":[97],"optimal":[99],"sublinear":[100],"regret":[101],"O(\u221aT)":[102],",":[103],"implying":[104],"learn":[112],"common":[114],"having":[116],"diminishing":[118],"gap":[119],"from":[120],"best":[122],"hindsight.":[125],"Our":[126],"analysis":[127],"also":[128],"reveals":[129],"yields":[132],"same":[134],"asymptotic":[135],"performance":[136],"as":[137],"state-of-the-art":[139],"centralized":[140],"approach":[141],"while":[142],"keeping":[143],"local":[144],"at":[146],"edge":[147],"learners.":[148],"Via":[149],"numerical":[150],"tests":[151],"real":[153],"datasets,":[154],"demonstrate":[156],"effectiveness":[158],"on":[163],"various":[164],"regression":[166],"time-series":[168],"prediction":[169],"tasks.":[170]},"counts_by_year":[{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}