{"id":"https://openalex.org/W4318186088","doi":"https://doi.org/10.1109/bigdata55660.2022.10020426","title":"A Convergence Theory for Federated Average: Beyond Smoothness","display_name":"A Convergence Theory for Federated Average: Beyond Smoothness","publication_year":2022,"publication_date":"2022-12-17","ids":{"openalex":"https://openalex.org/W4318186088","doi":"https://doi.org/10.1109/bigdata55660.2022.10020426"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata55660.2022.10020426","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata55660.2022.10020426","pdf_url":null,"source":{"id":"https://openalex.org/S4363607709","display_name":"2022 IEEE International Conference on Big Data (Big Data)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Conference on Big Data (Big Data)","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/A5100458648","display_name":"Xiaoxiao Li","orcid":"https://orcid.org/0000-0002-0376-5135"},"institutions":[{"id":"https://openalex.org/I1287378978","display_name":"University of British Columbia Hospital","ror":"https://ror.org/00frst980","country_code":"CA","type":"healthcare","lineage":["https://openalex.org/I1287378978","https://openalex.org/I141074466","https://openalex.org/I141074466","https://openalex.org/I141945490","https://openalex.org/I2799475292"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Xiaoxiao Li","raw_affiliation_strings":["UBC,Department of ECE,Vancouver,Canada","Department of ECE, UBC, Vancouver, Canada"],"affiliations":[{"raw_affiliation_string":"UBC,Department of ECE,Vancouver,Canada","institution_ids":["https://openalex.org/I1287378978"]},{"raw_affiliation_string":"Department of ECE, UBC, Vancouver, Canada","institution_ids":["https://openalex.org/I1287378978"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091070408","display_name":"Zhao Song","orcid":"https://orcid.org/0000-0002-5535-2789"},"institutions":[{"id":"https://openalex.org/I1306409833","display_name":"Adobe Systems (United States)","ror":"https://ror.org/059tvcg64","country_code":"US","type":"company","lineage":["https://openalex.org/I1306409833"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhao Song","raw_affiliation_strings":["Adobe Research Adobe,San Jose,USA","Adobe Research Adobe, San Jose, USA"],"affiliations":[{"raw_affiliation_string":"Adobe Research Adobe,San Jose,USA","institution_ids":["https://openalex.org/I1306409833"]},{"raw_affiliation_string":"Adobe Research Adobe, San Jose, USA","institution_ids":["https://openalex.org/I1306409833"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016831506","display_name":"Runzhou Tao","orcid":"https://orcid.org/0000-0002-3733-5168"},"institutions":[{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Runzhou Tao","raw_affiliation_strings":["Columbia University,Department of CS,New York,USA","Department of CS, Columbia University, New York, USA"],"affiliations":[{"raw_affiliation_string":"Columbia University,Department of CS,New York,USA","institution_ids":["https://openalex.org/I78577930"]},{"raw_affiliation_string":"Department of CS, Columbia University, New York, USA","institution_ids":["https://openalex.org/I78577930"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101487987","display_name":"Guangyi Zhang","orcid":"https://orcid.org/0000-0002-4476-5633"},"institutions":[{"id":"https://openalex.org/I5023651","display_name":"McGill University","ror":"https://ror.org/01pxwe438","country_code":"CA","type":"education","lineage":["https://openalex.org/I5023651"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Guangyi Zhang","raw_affiliation_strings":["McGill University,Department of ECE,Montreal,Canada","Department of ECE, McGill University, Montreal, Canada"],"affiliations":[{"raw_affiliation_string":"McGill University,Department of ECE,Montreal,Canada","institution_ids":["https://openalex.org/I5023651"]},{"raw_affiliation_string":"Department of ECE, McGill University, Montreal, Canada","institution_ids":["https://openalex.org/I5023651"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100458648"],"corresponding_institution_ids":["https://openalex.org/I1287378978"],"apc_list":null,"apc_paid":null,"fwci":0.3122,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.53989118,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1292","last_page":"1297"},"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":0.9995999932289124,"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/T10964","display_name":"Wireless Communication Security Techniques","score":0.9866999983787537,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/smoothness","display_name":"Smoothness","score":0.8798120021820068},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7593808174133301},{"id":"https://openalex.org/keywords/lipschitz-continuity","display_name":"Lipschitz continuity","score":0.7558526396751404},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.7021287083625793},{"id":"https://openalex.org/keywords/bounded-function","display_name":"Bounded function","score":0.6943733096122742},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.5284469127655029},{"id":"https://openalex.org/keywords/gradient-descent","display_name":"Gradient descent","score":0.5181878209114075},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.5151111483573914},{"id":"https://openalex.org/keywords/scheme","display_name":"Scheme (mathematics)","score":0.4689953625202179},{"id":"https://openalex.org/keywords/stochastic-gradient-descent","display_name":"Stochastic gradient descent","score":0.46793362498283386},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.46626004576683044},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.22799113392829895},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.16902846097946167},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.07635268568992615},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.06733590364456177}],"concepts":[{"id":"https://openalex.org/C102634674","wikidata":"https://www.wikidata.org/wiki/Q868473","display_name":"Smoothness","level":2,"score":0.8798120021820068},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7593808174133301},{"id":"https://openalex.org/C22324862","wikidata":"https://www.wikidata.org/wiki/Q652707","display_name":"Lipschitz continuity","level":2,"score":0.7558526396751404},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.7021287083625793},{"id":"https://openalex.org/C34388435","wikidata":"https://www.wikidata.org/wiki/Q2267362","display_name":"Bounded function","level":2,"score":0.6943733096122742},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.5284469127655029},{"id":"https://openalex.org/C153258448","wikidata":"https://www.wikidata.org/wiki/Q1199743","display_name":"Gradient descent","level":3,"score":0.5181878209114075},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.5151111483573914},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.4689953625202179},{"id":"https://openalex.org/C206688291","wikidata":"https://www.wikidata.org/wiki/Q7617819","display_name":"Stochastic gradient descent","level":3,"score":0.46793362498283386},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.46626004576683044},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.22799113392829895},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.16902846097946167},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.07635268568992615},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.06733590364456177},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata55660.2022.10020426","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata55660.2022.10020426","pdf_url":null,"source":{"id":"https://openalex.org/S4363607709","display_name":"2022 IEEE International Conference on Big Data (Big Data)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Conference on Big Data (Big Data)","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":50,"referenced_works":["https://openalex.org/W1726806267","https://openalex.org/W2064942524","https://openalex.org/W2530417694","https://openalex.org/W2807006176","https://openalex.org/W2900120080","https://openalex.org/W2900182564","https://openalex.org/W2904190483","https://openalex.org/W2924921501","https://openalex.org/W2940453604","https://openalex.org/W2950826569","https://openalex.org/W2955213239","https://openalex.org/W2963179579","https://openalex.org/W2963318081","https://openalex.org/W2966896250","https://openalex.org/W3006017224","https://openalex.org/W3015640161","https://openalex.org/W3021654819","https://openalex.org/W3040685212","https://openalex.org/W4206320562","https://openalex.org/W4212774754","https://openalex.org/W4226405495","https://openalex.org/W4287728383","https://openalex.org/W4288110237","https://openalex.org/W4288111766","https://openalex.org/W4288333953","https://openalex.org/W4318186088","https://openalex.org/W6684249991","https://openalex.org/W6728757088","https://openalex.org/W6738373677","https://openalex.org/W6752029299","https://openalex.org/W6752191696","https://openalex.org/W6755988804","https://openalex.org/W6756091659","https://openalex.org/W6757172675","https://openalex.org/W6758358981","https://openalex.org/W6759238902","https://openalex.org/W6761135920","https://openalex.org/W6765541894","https://openalex.org/W6766675127","https://openalex.org/W6767664422","https://openalex.org/W6768020840","https://openalex.org/W6772307254","https://openalex.org/W6773817997","https://openalex.org/W6774804355","https://openalex.org/W6780501606","https://openalex.org/W6784790197","https://openalex.org/W6789305514","https://openalex.org/W6796340207","https://openalex.org/W6811287140","https://openalex.org/W6840756468"],"related_works":["https://openalex.org/W3208021060","https://openalex.org/W2063845753","https://openalex.org/W2963794891","https://openalex.org/W4308243023","https://openalex.org/W1811750039","https://openalex.org/W3177586498","https://openalex.org/W2912745458","https://openalex.org/W3121625564","https://openalex.org/W3033855005","https://openalex.org/W4321014993"],"abstract_inverted_index":{"Federated":[0,25,151],"learning":[1],"enables":[2],"a":[3,12,19,46,141,146],"large":[4],"amount":[5],"of":[6,80,91],"edge":[7],"computing":[8],"devices":[9,38],"to":[10,53],"learn":[11],"model":[13],"without":[14],"data":[15],"sharing":[16],"jointly.":[17],"As":[18,140],"leading":[20],"algorithm":[21],"in":[22,34,45,113,135],"this":[23,74,143],"setting,":[24],"Average":[26],"(FedAvg),":[27],"which":[28,107,125],"runs":[29],"Stochastic":[30],"Gradient":[31],"Descent":[32],"(SGD)":[33],"parallel":[35],"on":[36,122,150],"local":[37],"and":[39,56,100],"averages":[40],"the":[41,78,84,89,98,104,123,129,136],"sequences":[42],"only":[43],"once":[44],"while,":[47],"have":[48,108],"been":[49],"widely":[50],"used":[51,131],"due":[52],"their":[54],"simplicity":[55],"low":[57],"communication":[58],"cost.":[59],"However,":[60],"despite":[61],"recent":[62],"research":[63],"efforts,":[64],"it":[65],"lacks":[66],"theoretical":[67,147],"analysis":[68,138],"under":[69],"assumptions":[70],"beyond":[71],"smoothness.":[72,93],"In":[73,116],"paper,":[75],"we":[76,87,96,118],"analyze":[77],"convergence":[79,137,148],"FedAvg.":[81],"Different":[82],"from":[83],"existing":[85],"work,":[86],"relax":[88],"assumption":[90,114,134],"strong":[92],"More":[94],"specifically,":[95],"assume":[97,120],"semi-smoothness":[99],"semi-Lipschitz":[101],"properties":[102],"for":[103],"loss":[105],"function,":[106],"an":[109],"additional":[110],"first-order":[111],"term":[112],"definitions.":[115],"addition,":[117],"also":[119],"bound":[121],"gradient,":[124],"is":[126],"weaker":[127],"than":[128],"commonly":[130],"bounded":[132],"gradient":[133],"scheme.":[139],"solution,":[142],"paper":[144],"provides":[145],"study":[149],"Learning.":[152]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}