{"id":"https://openalex.org/W4401508634","doi":"https://doi.org/10.1109/infocom52122.2024.10621361","title":"Fed-CVLC: Compressing Federated Learning Communications with Variable-Length Codes","display_name":"Fed-CVLC: Compressing Federated Learning Communications with Variable-Length Codes","publication_year":2024,"publication_date":"2024-05-20","ids":{"openalex":"https://openalex.org/W4401508634","doi":"https://doi.org/10.1109/infocom52122.2024.10621361"},"language":"en","primary_location":{"id":"doi:10.1109/infocom52122.2024.10621361","is_oa":false,"landing_page_url":"https://doi.org/10.1109/infocom52122.2024.10621361","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE INFOCOM 2024 - IEEE Conference on Computer Communications","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/A5107640657","display_name":"Xiaoxin Su","orcid":null},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xiaoxin Su","raw_affiliation_strings":["Shenzhen University,College of Computer Science and Software Engineering,Shenzhen,China"],"affiliations":[{"raw_affiliation_string":"Shenzhen University,College of Computer Science and Software Engineering,Shenzhen,China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5104240859","display_name":"Yipeng Zhou","orcid":null},"institutions":[{"id":"https://openalex.org/I99043593","display_name":"Macquarie University","ror":"https://ror.org/01sf06y89","country_code":"AU","type":"education","lineage":["https://openalex.org/I99043593"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Yipeng Zhou","raw_affiliation_strings":["Macquarie University,School of Computing, Faculty of Science and Engineering,Sydney,Australia"],"affiliations":[{"raw_affiliation_string":"Macquarie University,School of Computing, Faculty of Science and Engineering,Sydney,Australia","institution_ids":["https://openalex.org/I99043593"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002534955","display_name":"Laizhong Cui","orcid":"https://orcid.org/0000-0003-1991-290X"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Laizhong Cui","raw_affiliation_strings":["Shenzhen University,College of Computer Science and Software Engineering,Shenzhen,China"],"affiliations":[{"raw_affiliation_string":"Shenzhen University,College of Computer Science and Software Engineering,Shenzhen,China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068489266","display_name":"John C. S. Lui","orcid":"https://orcid.org/0000-0001-7466-0384"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"John C. S. Lui","raw_affiliation_strings":["The Chinese University of Hong Kong,Department of Computer Science and Engineering,HKSAR"],"affiliations":[{"raw_affiliation_string":"The Chinese University of Hong Kong,Department of Computer Science and Engineering,HKSAR","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5039311485","display_name":"Jiangchuan Liu","orcid":"https://orcid.org/0000-0001-6592-1984"},"institutions":[{"id":"https://openalex.org/I18014758","display_name":"Simon Fraser University","ror":"https://ror.org/0213rcc28","country_code":"CA","type":"education","lineage":["https://openalex.org/I18014758"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Jiangchuan Liu","raw_affiliation_strings":["Simon Fraser University,School of Computing Science,Canada"],"affiliations":[{"raw_affiliation_string":"Simon Fraser University,School of Computing Science,Canada","institution_ids":["https://openalex.org/I18014758"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5107640657"],"corresponding_institution_ids":["https://openalex.org/I180726961"],"apc_list":null,"apc_paid":null,"fwci":1.4464,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.84653013,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"601","last_page":"610"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":1.0,"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":1.0,"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":0.9973999857902527,"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/T10237","display_name":"Cryptography and Data Security","score":0.9957000017166138,"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":0.7341333031654358},{"id":"https://openalex.org/keywords/variable","display_name":"Variable (mathematics)","score":0.572014331817627},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10310977697372437}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7341333031654358},{"id":"https://openalex.org/C182365436","wikidata":"https://www.wikidata.org/wiki/Q50701","display_name":"Variable (mathematics)","level":2,"score":0.572014331817627},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10310977697372437},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/infocom52122.2024.10621361","is_oa":false,"landing_page_url":"https://doi.org/10.1109/infocom52122.2024.10621361","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE INFOCOM 2024 - IEEE Conference on Computer Communications","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320337504","display_name":"Research and Development","ror":"https://ror.org/027s68j25"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":44,"referenced_works":["https://openalex.org/W398859631","https://openalex.org/W569478347","https://openalex.org/W2194775991","https://openalex.org/W2332485628","https://openalex.org/W2535838896","https://openalex.org/W2766140019","https://openalex.org/W2769644379","https://openalex.org/W2912213068","https://openalex.org/W2963092133","https://openalex.org/W2963318081","https://openalex.org/W2989289980","https://openalex.org/W3015636663","https://openalex.org/W3015640161","https://openalex.org/W3047304572","https://openalex.org/W3124349893","https://openalex.org/W3152952112","https://openalex.org/W3155963862","https://openalex.org/W3156310591","https://openalex.org/W3201879251","https://openalex.org/W3208144977","https://openalex.org/W4221143748","https://openalex.org/W4226183928","https://openalex.org/W4283208007","https://openalex.org/W4283215441","https://openalex.org/W4283220690","https://openalex.org/W4310895557","https://openalex.org/W4318619660","https://openalex.org/W4385245566","https://openalex.org/W6683984541","https://openalex.org/W6728757088","https://openalex.org/W6728975057","https://openalex.org/W6738460352","https://openalex.org/W6745723224","https://openalex.org/W6746200960","https://openalex.org/W6746839373","https://openalex.org/W6748019269","https://openalex.org/W6754416507","https://openalex.org/W6763549698","https://openalex.org/W6765541894","https://openalex.org/W6779308105","https://openalex.org/W6780897730","https://openalex.org/W6783919029","https://openalex.org/W6789169260","https://openalex.org/W6790212648"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052","https://openalex.org/W2382290278","https://openalex.org/W4395014643"],"abstract_inverted_index":{"In":[0,85],"Federated":[1],"Learning":[2,110],"(FL)":[3],"paradigm,":[4],"a":[5,52,70,157],"parameter":[6],"server":[7],"(PS)":[8],"concurrently":[9],"communicates":[10],"with":[11,112,166,174],"distributed":[12],"participating":[13],"clients":[14,49],"for":[15,101,148],"model":[16,21,83,126,142,186],"collection,":[17],"update":[18],"aggregation,":[19],"and":[20,47,61,80,91,164],"distribution":[22],"over":[23],"multiple":[24],"rounds,":[25],"without":[26],"touching":[27],"private":[28],"data":[29,39],"owned":[30],"by":[31,188,194],"individual":[32],"clients.":[33],"FL":[34],"is":[35,99,155],"appealing":[36],"in":[37,103,120],"preserving":[38],"privacy;":[40],"yet":[41],"the":[42,45,78,117,123,135,141,146],"communication":[43,192],"between":[44],"PS":[46],"scattered":[48],"can":[50],"be":[51],"severe":[53],"bottleneck.":[54],"Model":[55],"compression":[56,102,159],"algorithms,":[57],"such":[58],"as":[59],"quantization":[60,163],"sparsification,":[62,165],"have":[63,171],"been":[64,172],"suggested":[65],"but":[66],"they":[67],"generally":[68],"assume":[69],"fixed":[71],"code":[72,118],"length,":[73],"which":[74,115],"does":[75],"not":[76],"reflect":[77],"heterogeneity":[79],"variability":[81],"of":[82,122,125],"updates.":[84,127],"this":[86],"paper,":[87],"through":[88],"both":[89],"analysis":[90],"experiments,":[92],"we":[93],"show":[94],"strong":[95],"evidences":[96],"that":[97,133,153,161,179],"variable-length":[98],"beneficial":[100],"FL.":[104],"We":[105,128,150],"accordingly":[106],"present":[107],"Fed-CVLC":[108,154,180],"(Federated":[109],"Compression":[111],"Variable-Length":[113],"Codes),":[114],"fine-tunes":[116],"length":[119],"response":[121],"dynamics":[124],"develop":[129],"optimal":[130],"tuning":[131],"strategy":[132],"minimizes":[134],"loss":[136],"function":[137],"(equivalent":[138],"to":[139,145,177],"maximizing":[140],"utility)":[143],"subject":[144],"budget":[147],"communication.":[149],"further":[151],"demonstrate":[152,178],"indeed":[156],"general":[158],"design":[160],"bridges":[162],"greater":[167],"flexibility.":[168],"Extensive":[169],"experiments":[170],"conducted":[173],"public":[175],"datasets":[176],"remarkably":[181],"outperforms":[182],"state-of-the-art":[183],"baselines,":[184],"improving":[185],"utility":[187],"1.50%-5.44%,":[189],"or":[190],"shrinking":[191],"traffic":[193],"16.67%-41.61%.":[195]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3}],"updated_date":"2026-03-12T08:34:05.389933","created_date":"2025-10-10T00:00:00"}