{"id":"https://openalex.org/W3114502420","doi":"https://doi.org/10.1109/vcip49819.2020.9301815","title":"Network Update Compression for Federated Learning","display_name":"Network Update Compression for Federated Learning","publication_year":2020,"publication_date":"2020-12-01","ids":{"openalex":"https://openalex.org/W3114502420","doi":"https://doi.org/10.1109/vcip49819.2020.9301815","mag":"3114502420"},"language":"en","primary_location":{"id":"doi:10.1109/vcip49819.2020.9301815","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vcip49819.2020.9301815","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Visual Communications and Image Processing (VCIP)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5036691509","display_name":"Birendra Kathariya","orcid":"https://orcid.org/0000-0001-9297-8978"},"institutions":[{"id":"https://openalex.org/I75421653","display_name":"University of Missouri\u2013Kansas City","ror":"https://ror.org/01w0d5g70","country_code":"US","type":"education","lineage":["https://openalex.org/I75421653"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Birendra Kathariya","raw_affiliation_strings":["University of Missouri-Kansas City, Kansas City, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Missouri-Kansas City, Kansas City, USA","institution_ids":["https://openalex.org/I75421653"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100361230","display_name":"Li Li","orcid":"https://orcid.org/0000-0002-7163-6263"},"institutions":[{"id":"https://openalex.org/I75421653","display_name":"University of Missouri\u2013Kansas City","ror":"https://ror.org/01w0d5g70","country_code":"US","type":"education","lineage":["https://openalex.org/I75421653"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Li Li","raw_affiliation_strings":["University of Missouri-Kansas City, Kansas City, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Missouri-Kansas City, Kansas City, USA","institution_ids":["https://openalex.org/I75421653"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100380625","display_name":"Zhu Li","orcid":"https://orcid.org/0000-0002-8246-177X"},"institutions":[{"id":"https://openalex.org/I75421653","display_name":"University of Missouri\u2013Kansas City","ror":"https://ror.org/01w0d5g70","country_code":"US","type":"education","lineage":["https://openalex.org/I75421653"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhu Li","raw_affiliation_strings":["University of Missouri-Kansas City, Kansas City, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Missouri-Kansas City, Kansas City, USA","institution_ids":["https://openalex.org/I75421653"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Lingyu Duan","orcid":null},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lingyu Duan","raw_affiliation_strings":["Peking University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100449791","display_name":"Shan Liu","orcid":"https://orcid.org/0000-0002-1442-1207"},"institutions":[{"id":"https://openalex.org/I70745867","display_name":"KLA (United States)","ror":"https://ror.org/02rqhpa98","country_code":"US","type":"company","lineage":["https://openalex.org/I70745867"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shan Liu","raw_affiliation_strings":["Tencent America, Palo Alto, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tencent America, Palo Alto, USA","institution_ids":["https://openalex.org/I70745867"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.115,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.41063835,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":93},"biblio":{"volume":"abs 1610 2132","issue":null,"first_page":"38","last_page":"41"},"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":0.9890000224113464,"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/T12879","display_name":"Distributed Sensor Networks and Detection Algorithms","score":0.9750000238418579,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8076853156089783},{"id":"https://openalex.org/keywords/telecommunications-link","display_name":"Telecommunications link","score":0.8069998621940613},{"id":"https://openalex.org/keywords/edge-device","display_name":"Edge device","score":0.6560028195381165},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5955761671066284},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.5440307259559631},{"id":"https://openalex.org/keywords/synchronizing","display_name":"Synchronizing","score":0.5234736204147339},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.4565219283103943},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.4212953448295593},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.4200354218482971},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4024907350540161},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.34529930353164673},{"id":"https://openalex.org/keywords/cloud-computing","display_name":"Cloud computing","score":0.09564560651779175},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.0882534384727478}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8076853156089783},{"id":"https://openalex.org/C138660444","wikidata":"https://www.wikidata.org/wiki/Q5607897","display_name":"Telecommunications link","level":2,"score":0.8069998621940613},{"id":"https://openalex.org/C138236772","wikidata":"https://www.wikidata.org/wiki/Q25098575","display_name":"Edge device","level":3,"score":0.6560028195381165},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5955761671066284},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.5440307259559631},{"id":"https://openalex.org/C162932704","wikidata":"https://www.wikidata.org/wiki/Q1058791","display_name":"Synchronizing","level":3,"score":0.5234736204147339},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.4565219283103943},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.4212953448295593},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.4200354218482971},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4024907350540161},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.34529930353164673},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.09564560651779175},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0882534384727478},{"id":"https://openalex.org/C761482","wikidata":"https://www.wikidata.org/wiki/Q118093","display_name":"Transmission (telecommunications)","level":2,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/vcip49819.2020.9301815","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vcip49819.2020.9301815","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Visual Communications and Image Processing (VCIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W2049633694","https://openalex.org/W2121775913","https://openalex.org/W2125389748","https://openalex.org/W2163107063","https://openalex.org/W2233116163","https://openalex.org/W2283463896","https://openalex.org/W2407022425","https://openalex.org/W2531786980","https://openalex.org/W2535838896","https://openalex.org/W2541884796","https://openalex.org/W2606891064","https://openalex.org/W2617766261","https://openalex.org/W2774000609","https://openalex.org/W2912213068","https://openalex.org/W2920965512","https://openalex.org/W2963803379","https://openalex.org/W2964004663","https://openalex.org/W3101036738","https://openalex.org/W4297687186","https://openalex.org/W4318619660","https://openalex.org/W6678583879","https://openalex.org/W6689694917","https://openalex.org/W6695838908","https://openalex.org/W6714239094","https://openalex.org/W6728495017","https://openalex.org/W6728757088","https://openalex.org/W6738460352","https://openalex.org/W6746839373"],"related_works":["https://openalex.org/W2359328895","https://openalex.org/W2007402811","https://openalex.org/W2363535981","https://openalex.org/W2326762630","https://openalex.org/W2391354408","https://openalex.org/W2166562438","https://openalex.org/W2388558702","https://openalex.org/W2349570115","https://openalex.org/W2347535056","https://openalex.org/W1986103452"],"abstract_inverted_index":{"In":[0,67],"federated":[1,161],"learning":[2,162],"setting,":[3],"models":[4,148],"are":[5,30,37,62],"trained":[6],"in":[7,21,49,160],"a":[8,69,84],"variety":[9],"of":[10,53,76,113],"edge-devices":[11],"with":[12,55,138],"locally":[13],"generated":[14],"data":[15],"and":[16,58,61,78,135],"each":[17],"round":[18],"only":[19],"updates":[20,90],"the":[22,27,33,92,110,150,156],"current":[23],"model":[24,28,152],"rather":[25],"than":[26],"itself":[29],"sent":[31],"to":[32,39,83,91,102,127],"server":[34],"where":[35],"they":[36],"aggregated":[38],"compose":[40],"an":[41,73,98],"improved":[42],"model.":[43],"These":[44],"edge":[45],"devices,":[46],"however,":[47],"reside":[48],"highly":[50],"uneven":[51],"nature":[52,75],"network":[54,70,146],"higher":[56],"latency":[57],"lower-throughput":[59],"connections":[60],"intermittently":[63],"available":[64],"for":[65,116],"training.":[66],"addition,":[68],"connection":[71],"has":[72],"asymmetric":[74],"downlink":[77],"uplink.":[79],"All":[80],"these":[81,89],"contribute":[82],"major":[85],"challenge":[86],"while":[87,163],"synchronizing":[88],"server.In":[93],"this":[94],"work,":[95],"we":[96],"proposed":[97,151],"efficient":[99],"coding":[100],"solution":[101],"significantly":[103,154],"reduce":[104,155],"uplink":[105,157],"communication":[106,158],"cost":[107,159],"by":[108,121],"reducing":[109],"total":[111],"number":[112],"parameters":[114],"required":[115],"updates.":[117],"This":[118],"was":[119],"achieved":[120],"applying":[122],"Gaussian":[123],"Mixture":[124],"Model":[125],"(GMM)":[126],"localize":[128],"Karhunen-Lo\u00e8ve":[129],"Transform":[130],"(KLT)":[131],"on":[132,143],"inter-model":[133],"subspace":[134],"representing":[136],"it":[137],"two":[139],"low-rank":[140],"matrices.":[141],"Experiments":[142],"convolutional":[144],"neural":[145],"(CNN)":[147],"showed":[149],"can":[153],"preserving":[164],"reasonable":[165],"accuracy.":[166]},"counts_by_year":[{"year":2021,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}