{"id":"https://openalex.org/W4323644139","doi":"https://doi.org/10.1109/jiot.2023.3253813","title":"Federated Learning Hyperparameter Tuning From a System Perspective","display_name":"Federated Learning Hyperparameter Tuning From a System Perspective","publication_year":2023,"publication_date":"2023-03-08","ids":{"openalex":"https://openalex.org/W4323644139","doi":"https://doi.org/10.1109/jiot.2023.3253813"},"language":"en","primary_location":{"id":"doi:10.1109/jiot.2023.3253813","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jiot.2023.3253813","pdf_url":null,"source":{"id":"https://openalex.org/S2480266640","display_name":"IEEE Internet of Things Journal","issn_l":"2327-4662","issn":["2327-4662","2372-2541"],"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 Internet of Things Journal","raw_type":"journal-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/A5033390700","display_name":"Huanle Zhang","orcid":"https://orcid.org/0000-0002-3928-7753"},"institutions":[{"id":"https://openalex.org/I80143920","display_name":"Shandong University of Science and Technology","ror":"https://ror.org/04gtjhw98","country_code":"CN","type":"education","lineage":["https://openalex.org/I80143920"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huanle Zhang","raw_affiliation_strings":["School of Computer Science and Technology, Shandong University, Jinan, China"],"raw_orcid":"https://orcid.org/0000-0002-3928-7753","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Shandong University, Jinan, China","institution_ids":["https://openalex.org/I80143920"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071723684","display_name":"Lei Fu","orcid":"https://orcid.org/0000-0002-0575-6128"},"institutions":[{"id":"https://openalex.org/I917184967","display_name":"Bank of China","ror":"https://ror.org/02mt4s337","country_code":"CN","type":"other","lineage":["https://openalex.org/I917184967"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lei Fu","raw_affiliation_strings":["Center for Capital Operation, Bank of Jiangsu, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Center for Capital Operation, Bank of Jiangsu, Nanjing, China","institution_ids":["https://openalex.org/I917184967"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100659123","display_name":"Mi Zhang","orcid":"https://orcid.org/0000-0001-7002-6757"},"institutions":[{"id":"https://openalex.org/I52357470","display_name":"The Ohio State University","ror":"https://ror.org/00rs6vg23","country_code":"US","type":"education","lineage":["https://openalex.org/I52357470"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mi Zhang","raw_affiliation_strings":["Department of Computer Science and Engineering, Ohio State University, Columbus, OH, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Ohio State University, Columbus, OH, USA","institution_ids":["https://openalex.org/I52357470"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100703619","display_name":"Pengfei Hu","orcid":"https://orcid.org/0000-0002-7935-886X"},"institutions":[{"id":"https://openalex.org/I80143920","display_name":"Shandong University of Science and Technology","ror":"https://ror.org/04gtjhw98","country_code":"CN","type":"education","lineage":["https://openalex.org/I80143920"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Pengfei Hu","raw_affiliation_strings":["School of Computer Science and Technology, Shandong University, Jinan, China"],"raw_orcid":"https://orcid.org/0000-0002-7935-886X","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Shandong University, Jinan, China","institution_ids":["https://openalex.org/I80143920"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100692488","display_name":"Xiuzhen Cheng","orcid":"https://orcid.org/0000-0001-5912-4647"},"institutions":[{"id":"https://openalex.org/I80143920","display_name":"Shandong University of Science and Technology","ror":"https://ror.org/04gtjhw98","country_code":"CN","type":"education","lineage":["https://openalex.org/I80143920"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiuzhen Cheng","raw_affiliation_strings":["School of Computer Science and Technology, Shandong University, Jinan, China"],"raw_orcid":"https://orcid.org/0000-0001-5912-4647","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Shandong University, Jinan, China","institution_ids":["https://openalex.org/I80143920"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086439160","display_name":"Prasant Mohapatra","orcid":"https://orcid.org/0000-0002-2768-5308"},"institutions":[{"id":"https://openalex.org/I84218800","display_name":"University of California, Davis","ror":"https://ror.org/05rrcem69","country_code":"US","type":"education","lineage":["https://openalex.org/I84218800"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Prasant Mohapatra","raw_affiliation_strings":["Department of Computer Science, University of California, Davis, Davis, CA, USA"],"raw_orcid":"https://orcid.org/0000-0002-2768-5308","affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of California, Davis, Davis, CA, USA","institution_ids":["https://openalex.org/I84218800"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100352241","display_name":"Xin Liu","orcid":"https://orcid.org/0000-0002-5379-8269"},"institutions":[{"id":"https://openalex.org/I84218800","display_name":"University of California, Davis","ror":"https://ror.org/05rrcem69","country_code":"US","type":"education","lineage":["https://openalex.org/I84218800"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xin Liu","raw_affiliation_strings":["Department of Computer Science, University of California, Davis, Davis, CA, USA"],"raw_orcid":"https://orcid.org/0000-0002-5379-8269","affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of California, Davis, Davis, CA, USA","institution_ids":["https://openalex.org/I84218800"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":2345,"currency":"USD","value_usd":2345},"apc_paid":null,"fwci":1.9705,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":{"value":0.88429766,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":93,"max":99},"biblio":{"volume":"10","issue":"16","first_page":"14102","last_page":"14113"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","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/T10764","display_name":"Privacy-Preserving Technologies in Data","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/T13918","display_name":"Advanced Data and IoT Technologies","score":0.9825000166893005,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"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/T11598","display_name":"Internet Traffic Analysis and Secure E-voting","score":0.972100019454956,"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/computer-science","display_name":"Computer science","score":0.8471524715423584},{"id":"https://openalex.org/keywords/hyperparameter","display_name":"Hyperparameter","score":0.8447350263595581},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.767414927482605},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.5700669884681702},{"id":"https://openalex.org/keywords/perspective","display_name":"Perspective (graphical)","score":0.517094612121582},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5099278688430786},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.45875242352485657},{"id":"https://openalex.org/keywords/transmission","display_name":"Transmission (telecommunications)","score":0.45808565616607666},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.4554975628852844},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.44950640201568604},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.4441908597946167},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.43633633852005005},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.42435675859451294},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.16360551118850708},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.10448828339576721}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8471524715423584},{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.8447350263595581},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.767414927482605},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.5700669884681702},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.517094612121582},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5099278688430786},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.45875242352485657},{"id":"https://openalex.org/C761482","wikidata":"https://www.wikidata.org/wiki/Q118093","display_name":"Transmission (telecommunications)","level":2,"score":0.45808565616607666},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.4554975628852844},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44950640201568604},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.4441908597946167},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.43633633852005005},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.42435675859451294},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.16360551118850708},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.10448828339576721},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","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},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/jiot.2023.3253813","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jiot.2023.3253813","pdf_url":null,"source":{"id":"https://openalex.org/S2480266640","display_name":"IEEE Internet of Things Journal","issn_l":"2327-4662","issn":["2327-4662","2372-2541"],"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 Internet of Things Journal","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.550000011920929,"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure"}],"awards":[{"id":"https://openalex.org/G1162667442","display_name":"Track-D: Data-Driven Disease Prevention and Control in Animal Health","funder_award_id":"2134901","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G3110218756","display_name":null,"funder_award_id":"USDA/NIFA 2020-67021-32855","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G3789803274","display_name":"BIGDATA: IA: A multi-level approach for global optimization of the surveillance and control of infectious disease in the swine industry","funder_award_id":"1838207","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G3841099640","display_name":"CNS Core: Medium: Collaborative:  Exploring and Exploiting Learning for Efficient Network Control: Non-Stationarity,  Inter-Dependence, and Domain-Knowledge","funder_award_id":"1901218","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G4959332381","display_name":null,"funder_award_id":"62202276","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5385193388","display_name":null,"funder_award_id":"2021YFB3100400","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G8942805157","display_name":null,"funder_award_id":"62232010","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":62,"referenced_works":["https://openalex.org/W1901616594","https://openalex.org/W2126559945","https://openalex.org/W2131241448","https://openalex.org/W2194775991","https://openalex.org/W2734358244","https://openalex.org/W2797583228","https://openalex.org/W2900120080","https://openalex.org/W2903150425","https://openalex.org/W2955213239","https://openalex.org/W2963815651","https://openalex.org/W2979917379","https://openalex.org/W2983144534","https://openalex.org/W2995978786","https://openalex.org/W2996999545","https://openalex.org/W3012125688","https://openalex.org/W3018835489","https://openalex.org/W3036550469","https://openalex.org/W3038022836","https://openalex.org/W3038028469","https://openalex.org/W3043723611","https://openalex.org/W3045004532","https://openalex.org/W3093708494","https://openalex.org/W3118608800","https://openalex.org/W3120697286","https://openalex.org/W3129405170","https://openalex.org/W3168047084","https://openalex.org/W3174943464","https://openalex.org/W3178336997","https://openalex.org/W3206389158","https://openalex.org/W3212637480","https://openalex.org/W3213321731","https://openalex.org/W4221141759","https://openalex.org/W4225874663","https://openalex.org/W4226361207","https://openalex.org/W4281867538","https://openalex.org/W4286909438","https://openalex.org/W4287122979","https://openalex.org/W4299283926","https://openalex.org/W4306178637","https://openalex.org/W4318619660","https://openalex.org/W6678664249","https://openalex.org/W6678911119","https://openalex.org/W6728757088","https://openalex.org/W6730169791","https://openalex.org/W6750665317","https://openalex.org/W6755988804","https://openalex.org/W6759226220","https://openalex.org/W6759238902","https://openalex.org/W6765541894","https://openalex.org/W6772643563","https://openalex.org/W6773976177","https://openalex.org/W6780008666","https://openalex.org/W6781318954","https://openalex.org/W6784106160","https://openalex.org/W6787972765","https://openalex.org/W6790640957","https://openalex.org/W6795916790","https://openalex.org/W6797529314","https://openalex.org/W6798417033","https://openalex.org/W6803118286","https://openalex.org/W6811113950","https://openalex.org/W6838425662"],"related_works":["https://openalex.org/W2140186469","https://openalex.org/W4390421286","https://openalex.org/W4280563792","https://openalex.org/W4389724018","https://openalex.org/W4318719684","https://openalex.org/W4318559728","https://openalex.org/W3183136280","https://openalex.org/W2775233965","https://openalex.org/W3114716045","https://openalex.org/W4360995913"],"abstract_inverted_index":{"Federated":[0],"learning":[1],"(FL)":[2],"is":[3,127,157],"a":[4,65],"distributed":[5],"model":[6],"training":[7,36,41,75,103,151],"paradigm":[8],"that":[9,126],"preserves":[10],"clients\u2019":[11],"data":[12],"privacy.":[13],"It":[14],"has":[15],"gained":[16],"tremendous":[17],"attention":[18],"from":[19],"both":[20],"academia":[21],"and":[22,32,52,104,120,129],"industry.":[23],"FL":[24,62,69,84,95,99,102,111,121,140,145,150],"hyper-parameters":[25,63,100],"(e.g.,":[26],"the":[27,33,40,56],"number":[28,34],"of":[29,35,45,59,116,156],"selected":[30],"clients":[31],"passes)":[37],"significantly":[38],"affect":[39],"overhead":[42,134],"in":[43,94,147],"terms":[44],"computation":[46,50],"time,":[47,49],"transmission":[48,53],"load,":[51],"load.":[54],"However,":[55],"current":[57],"practice":[58],"manually":[60],"selecting":[61],"imposes":[64],"heavy":[66],"burden":[67],"on":[68],"practitioners":[70,146],"because":[71],"applications":[72,119],"have":[73],"different":[74],"preferences.":[76],"In":[77],"this":[78],"paper,":[79],"we":[80,124],"propose,":[81],"an":[82],"automatic":[83],"hyper-parameter":[85],"tuning":[86],"algorithm":[87],"tailored":[88],"to":[89,137],"applications\u2019":[90],"diverse":[91,118],"system":[92,133],"requirements":[93],"training.":[96],"iteratively":[97],"adjusts":[98],"during":[101],"can":[105],"be":[106],"easily":[107],"integrated":[108],"into":[109],"existing":[110],"systems.":[112],"Through":[113],"extensive":[114],"evaluations":[115],"for":[117],"aggregation":[122],"algorithms,":[123],"show":[125],"lightweight":[128],"effective,":[130],"achieving":[131],"8.48%-26.75%":[132],"reduction":[135],"compared":[136],"using":[138],"fixed":[139],"hyper-parameters.":[141],"This":[142],"paper":[143],"assists":[144],"designing":[148],"high-performance":[149],"solutions.":[152],"The":[153],"source":[154],"code":[155],"available":[158],"at.":[159]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":5}],"updated_date":"2026-08-28T12:50:07.497085","created_date":"2025-10-10T00:00:00"}