{"id":"https://openalex.org/W4396982426","doi":"https://doi.org/10.1109/tmc.2024.3402080","title":"Adaptive Federated Learning via New Entropy Approach","display_name":"Adaptive Federated Learning via New Entropy Approach","publication_year":2024,"publication_date":"2024-05-16","ids":{"openalex":"https://openalex.org/W4396982426","doi":"https://doi.org/10.1109/tmc.2024.3402080"},"language":"en","primary_location":{"id":"doi:10.1109/tmc.2024.3402080","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmc.2024.3402080","pdf_url":null,"source":{"id":"https://openalex.org/S69141925","display_name":"IEEE Transactions on Mobile Computing","issn_l":"1536-1233","issn":["1536-1233","1558-0660","2161-9875"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Mobile Computing","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/A5037934577","display_name":"Shensheng Zheng","orcid":"https://orcid.org/0000-0002-2951-3737"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Shensheng Zheng","raw_affiliation_strings":["School of Artificial Intelligence, Sun Yat-sen University, Zhuhai, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Sun Yat-sen University, Zhuhai, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101899177","display_name":"Wenhao Yuan","orcid":"https://orcid.org/0009-0001-6625-7496"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenhao Yuan","raw_affiliation_strings":["School of Artificial Intelligence, Sun Yat-sen University, Zhuhai, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Sun Yat-sen University, Zhuhai, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078667038","display_name":"Xuehe Wang","orcid":"https://orcid.org/0000-0002-6910-468X"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuehe Wang","raw_affiliation_strings":["School of Artificial Intelligence, Sun Yat-sen University, Zhuhai, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Sun Yat-sen University, Zhuhai, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5007119869","display_name":"Lingjie Duan","orcid":"https://orcid.org/0000-0002-0217-6507"},"institutions":[{"id":"https://openalex.org/I152815399","display_name":"Singapore University of Technology and Design","ror":"https://ror.org/05j6fvn87","country_code":"SG","type":"education","lineage":["https://openalex.org/I152815399"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Lingjie Duan","raw_affiliation_strings":["Pillar of Engineering Systems and Design, Singapore University of Technology and Design, Singapore"],"affiliations":[{"raw_affiliation_string":"Pillar of Engineering Systems and Design, Singapore University of Technology and Design, Singapore","institution_ids":["https://openalex.org/I152815399"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5037934577"],"corresponding_institution_ids":["https://openalex.org/I157773358"],"apc_list":null,"apc_paid":null,"fwci":5.2127,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":{"value":0.95954844,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"23","issue":"12","first_page":"11920","last_page":"11936"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9872999787330627,"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":0.9872999787330627,"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/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.9531999826431274,"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/T10203","display_name":"Recommender Systems and Techniques","score":0.9146000146865845,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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":0.8577673435211182},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.44344037771224976},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.35669654607772827},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.3370106816291809},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3206879198551178}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8577673435211182},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.44344037771224976},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.35669654607772827},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.3370106816291809},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3206879198551178},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tmc.2024.3402080","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmc.2024.3402080","pdf_url":null,"source":{"id":"https://openalex.org/S69141925","display_name":"IEEE Transactions on Mobile Computing","issn_l":"1536-1233","issn":["1536-1233","1558-0660","2161-9875"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Mobile Computing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G6893990029","display_name":null,"funder_award_id":"62206320","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320320751","display_name":"Ministry of Education - Singapore","ror":"https://ror.org/01kcva023"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":70,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W2083246371","https://openalex.org/W2107843968","https://openalex.org/W2112269233","https://openalex.org/W2112796928","https://openalex.org/W2118537510","https://openalex.org/W2513010757","https://openalex.org/W2734358244","https://openalex.org/W2767079719","https://openalex.org/W2798720628","https://openalex.org/W2807006176","https://openalex.org/W2900120080","https://openalex.org/W2912213068","https://openalex.org/W2920095265","https://openalex.org/W2963179579","https://openalex.org/W2963318081","https://openalex.org/W2972570881","https://openalex.org/W2989289980","https://openalex.org/W2998045710","https://openalex.org/W3045638580","https://openalex.org/W3080934299","https://openalex.org/W3095540342","https://openalex.org/W3100742445","https://openalex.org/W3100779497","https://openalex.org/W3105122387","https://openalex.org/W3110962653","https://openalex.org/W3113075536","https://openalex.org/W3114728946","https://openalex.org/W3118608800","https://openalex.org/W3136338303","https://openalex.org/W3137762252","https://openalex.org/W3170790803","https://openalex.org/W3170906335","https://openalex.org/W3184838508","https://openalex.org/W3200223987","https://openalex.org/W3203503583","https://openalex.org/W3205260830","https://openalex.org/W3213802103","https://openalex.org/W3213815372","https://openalex.org/W4206414320","https://openalex.org/W4285876308","https://openalex.org/W4306178637","https://openalex.org/W4312660260","https://openalex.org/W4378438552","https://openalex.org/W4385338532","https://openalex.org/W4385627109","https://openalex.org/W4385627407","https://openalex.org/W4385768077","https://openalex.org/W4385800841","https://openalex.org/W4386071762","https://openalex.org/W4386280757","https://openalex.org/W6637373629","https://openalex.org/W6676963778","https://openalex.org/W6677600329","https://openalex.org/W6728757088","https://openalex.org/W6752029299","https://openalex.org/W6752191696","https://openalex.org/W6755988804","https://openalex.org/W6756287877","https://openalex.org/W6759238902","https://openalex.org/W6760214840","https://openalex.org/W6762626082","https://openalex.org/W6767676916","https://openalex.org/W6773817997","https://openalex.org/W6773976177","https://openalex.org/W6779269186","https://openalex.org/W6787972765","https://openalex.org/W6790034021","https://openalex.org/W6796096428","https://openalex.org/W6796615672"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W3046775127","https://openalex.org/W3107602296","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W4364306694","https://openalex.org/W4312192474","https://openalex.org/W4283697347"],"abstract_inverted_index":{"Federated":[0],"Learning":[1],"(FL)":[2],"has":[3],"emerged":[4],"as":[5,48,76,135],"a":[6,19,77,132,150,253],"prominent":[7],"distributed":[8],"machine":[9],"learning":[10,92,126,152,197],"framework":[11],"that":[12,234],"enables":[13],"geographically":[14],"discrete":[15],"clients":[16,106,142],"to":[17,30,57,63,99,164],"train":[18],"global":[20],"model":[21,61],"collaboratively":[22],"while":[23],"preserving":[24],"their":[25],"privacy-sensitive":[26],"data.":[27],"However,":[28],"due":[29],"the":[31,39,42,55,65,82,101,113,123,144,161,166,181,186,191,194,206,210,224],"non-independent-and-identically-distributed":[32],"(Non-IID)":[33],"data":[34,114],"generated":[35],"by":[36,73,204],"heterogeneous":[37,105,120],"clients,":[38,121],"performances":[40],"of":[41,68,84,119,185,213],"conventional":[43],"federated":[44],"optimization":[45],"schemes":[46],"such":[47],"FedAvg":[49,239],"and":[50,107,116,183,231,240,246,251],"its":[51,241],"variants":[52,242],"deteriorate,":[53],"requiring":[54],"design":[56],"adaptively":[58],"adjust":[59],"specific":[60],"parameters":[62],"alleviate":[64,100],"negative":[66],"influence":[67],"heterogeneity.":[69],"In":[70],"this":[71],"paper,":[72],"leveraging":[74],"entropy":[75],"new":[78],"metric":[79],"for":[80,128,154,199],"assessing":[81],"degree":[83],"system":[85],"disorder,":[86],"we":[87,158,175],"propose":[88],"an":[89],"adaptive":[90,196],"FEDerated":[91],"algorithm":[93,237],"based":[94],"on":[95,180,190,223],"ENTropy":[96],"theory":[97],"(FedEnt)":[98],"parameter":[102,117],"deviation":[103,118],"among":[104,140],"achieve":[108],"fast":[109],"convergence.":[110],"Nevertheless,":[111],"given":[112],"disparity":[115],"determining":[122],"optimal":[124],"dynamic":[125],"rate":[127,153,198,212],"each":[129,155,200],"client":[130,201],"becomes":[131],"challenging":[133],"task":[134],"there":[136],"is":[137,202,217],"no":[138],"communication":[139],"participating":[141,156],"during":[143],"local":[145,172],"training":[146],"epochs.":[147],"To":[148],"enable":[149],"decentralized":[151],"client,":[157],"first":[159],"introduce":[160],"mean-field":[162,187,192],"terms":[163],"estimate":[165],"components":[167],"associated":[168],"with":[169],"other":[170],"clients\u2019":[171],"parameters.":[173],"Furthermore,":[174],"provide":[176],"rigorous":[177],"theoretical":[178],"analysis":[179],"existence":[182],"determination":[184],"estimators.":[188],"Based":[189],"estimators,":[193],"closed-form":[195],"derived":[203],"constructing":[205],"Hamilton":[207],"equation.":[208],"Moreover,":[209],"convergence":[211,255],"our":[214,235],"proposed":[215],"FedEnt":[216,236],"proved.":[218],"The":[219],"extensive":[220],"experimental":[221],"results":[222],"real-world":[225],"datasets":[226],"(i.e.,":[227,243],"MNIST,":[228],"EMNIST-L,":[229],"CIFAR10,":[230],"CIFAR100)":[232],"show":[233],"surpasses":[238],"FedAdam,":[244],"FedProx,":[245],"FedDyn)":[247],"under":[248],"Non-IID":[249],"settings":[250],"achieves":[252],"faster":[254],"rate.":[256]},"counts_by_year":[{"year":2025,"cited_by_count":12},{"year":2024,"cited_by_count":3}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
