{"id":"https://openalex.org/W4403182622","doi":"https://doi.org/10.1109/spawc60668.2024.10694371","title":"Partial Model Pruning and Personalization for Wireless Federated Learning","display_name":"Partial Model Pruning and Personalization for Wireless Federated Learning","publication_year":2024,"publication_date":"2024-09-10","ids":{"openalex":"https://openalex.org/W4403182622","doi":"https://doi.org/10.1109/spawc60668.2024.10694371"},"language":"en","primary_location":{"id":"doi:10.1109/spawc60668.2024.10694371","is_oa":false,"landing_page_url":"https://doi.org/10.1109/spawc60668.2024.10694371","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 25th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)","raw_type":"proceedings-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/A5100684378","display_name":"Xiaonan Liu","orcid":"https://orcid.org/0000-0002-5558-6067"},"institutions":[{"id":"https://openalex.org/I195460627","display_name":"University of Aberdeen","ror":"https://ror.org/016476m91","country_code":"GB","type":"education","lineage":["https://openalex.org/I195460627"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Xiaonan Liu","raw_affiliation_strings":["University of Aberdeen,School of Natural and Computing Science,UK"],"affiliations":[{"raw_affiliation_string":"University of Aberdeen,School of Natural and Computing Science,UK","institution_ids":["https://openalex.org/I195460627"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091847007","display_name":"Tharmalingam Ratnarajah","orcid":"https://orcid.org/0000-0002-7636-1246"},"institutions":[{"id":"https://openalex.org/I98677209","display_name":"University of Edinburgh","ror":"https://ror.org/01nrxwf90","country_code":"GB","type":"education","lineage":["https://openalex.org/I98677209"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Tharmalingam Ratnarajah","raw_affiliation_strings":["The University of Edinburgh,School of Engineering,UK"],"affiliations":[{"raw_affiliation_string":"The University of Edinburgh,School of Engineering,UK","institution_ids":["https://openalex.org/I98677209"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071345719","display_name":"Mathini Sellathurai","orcid":"https://orcid.org/0000-0002-8738-8583"},"institutions":[{"id":"https://openalex.org/I32062511","display_name":"Heriot-Watt University","ror":"https://ror.org/04mghma93","country_code":"GB","type":"education","lineage":["https://openalex.org/I32062511"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Mathini Sellathurai","raw_affiliation_strings":["Heriot-Watt University,Department of Engineering and Physical Science,Edinburgh,UK"],"affiliations":[{"raw_affiliation_string":"Heriot-Watt University,Department of Engineering and Physical Science,Edinburgh,UK","institution_ids":["https://openalex.org/I32062511"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5005913897","display_name":"Yonina C. Eldar","orcid":"https://orcid.org/0000-0003-4358-5304"},"institutions":[{"id":"https://openalex.org/I53964585","display_name":"Weizmann Institute of Science","ror":"https://ror.org/0316ej306","country_code":"IL","type":"education","lineage":["https://openalex.org/I53964585"]}],"countries":["IL"],"is_corresponding":false,"raw_author_name":"Yonina C. Eldar","raw_affiliation_strings":["Weizmann Institute of Science,Faculty of Mathematics and Computer Science,Israel"],"affiliations":[{"raw_affiliation_string":"Weizmann Institute of Science,Faculty of Mathematics and Computer Science,Israel","institution_ids":["https://openalex.org/I53964585"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100684378"],"corresponding_institution_ids":["https://openalex.org/I195460627"],"apc_list":null,"apc_paid":null,"fwci":0.3862,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.67870539,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"31","last_page":"35"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9447000026702881,"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":0.9447000026702881,"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/personalization","display_name":"Personalization","score":0.8043640851974487},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7832491397857666},{"id":"https://openalex.org/keywords/pruning","display_name":"Pruning","score":0.6644273996353149},{"id":"https://openalex.org/keywords/wireless","display_name":"Wireless","score":0.5411157011985779},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3389432728290558},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.3229962885379791},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.2746938467025757},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.15753412246704102}],"concepts":[{"id":"https://openalex.org/C183003079","wikidata":"https://www.wikidata.org/wiki/Q1000371","display_name":"Personalization","level":2,"score":0.8043640851974487},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7832491397857666},{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.6644273996353149},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.5411157011985779},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3389432728290558},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.3229962885379791},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.2746938467025757},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.15753412246704102},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C6557445","wikidata":"https://www.wikidata.org/wiki/Q173113","display_name":"Agronomy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/spawc60668.2024.10694371","is_oa":false,"landing_page_url":"https://doi.org/10.1109/spawc60668.2024.10694371","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 25th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320334627","display_name":"Engineering and Physical Sciences Research Council","ror":"https://ror.org/0439y7842"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":7,"referenced_works":["https://openalex.org/W2965862774","https://openalex.org/W2977090839","https://openalex.org/W3148526481","https://openalex.org/W4300806676","https://openalex.org/W4387682250","https://openalex.org/W4388505416","https://openalex.org/W6810249531"],"related_works":["https://openalex.org/W2109940557","https://openalex.org/W2466832359","https://openalex.org/W4391210591","https://openalex.org/W1582019636","https://openalex.org/W1499005795","https://openalex.org/W3172493050","https://openalex.org/W4385420271","https://openalex.org/W4312192618","https://openalex.org/W2593798266","https://openalex.org/W4385414918"],"abstract_inverted_index":{"To":[0,103],"address":[1],"the":[2,32,64,78,97,105,120,131],"heterogeneity":[3],"of":[4,14,96,139],"devices\u2019":[5],"data":[6,48],"and":[7,11,27,50,73,76,85,91,94,108,123,143],"guarantee":[8,109],"high":[9],"computation":[10,72,90,142],"communication":[12,74,92,144],"efficiency":[13],"federated":[15],"learning":[16,33,79,110],"(FL),":[17],"we":[18],"consider":[19],"an":[20],"FL":[21,68,99,133,148],"framework":[22,30,100,134],"with":[23,39,43,83,147,149],"partial":[24,150],"model":[25,34,40,65,151],"pruning":[26,41,121],"personalization.":[28,152],"This":[29],"splits":[31],"into":[35],"a":[36,51,58,136],"global":[37],"part":[38,53],"shared":[42],"all":[44],"devices":[45,82],"to":[46,54,69,117],"learn":[47],"representations":[49],"personalized":[52],"be":[55],"fine-tuned":[56],"for":[57,81],"specific":[59],"device.":[60],"It":[61],"can":[62],"adapt":[63],"size":[66],"during":[67],"reduce":[70],"both":[71],"latency":[75,93,145],"increases":[77],"accuracy":[80],"non-independent":[84],"identically":[86],"distributed":[87],"data.":[88],"The":[89],"convergence":[95,106],"proposed":[98,132],"are":[101,115],"analyzed.":[102],"maximize":[104],"rate":[107],"accuracy,":[111],"Karush\u2013Kuhn\u2013Tucker":[112],"(KKT)":[113],"conditions":[114],"deployed":[116],"jointly":[118],"optimize":[119],"ratio":[122],"bandwidth":[124],"allocation.":[125],"Finally,":[126],"experimental":[127],"results":[128],"demonstrate":[129],"that":[130],"achieves":[135],"remarkable":[137],"reduction":[138],"approximately":[140],"50%":[141],"compared":[146]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-12-27T23:08:20.325037","created_date":"2025-10-10T00:00:00"}