{"id":"https://openalex.org/W4220934571","doi":"https://doi.org/10.1145/3517207.3526969","title":"Empirical analysis of federated learning in heterogeneous environments","display_name":"Empirical analysis of federated learning in heterogeneous environments","publication_year":2022,"publication_date":"2022-03-29","ids":{"openalex":"https://openalex.org/W4220934571","doi":"https://doi.org/10.1145/3517207.3526969"},"language":"en","primary_location":{"id":"doi:10.1145/3517207.3526969","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3517207.3526969","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2nd European Workshop on Machine Learning and Systems","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://qmro.qmul.ac.uk/xmlui/bitstream/123456789/79664/2/Mohamed%20Empirical%20analysis%20of%202022%20Accepted.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5070017771","display_name":"Ahmed M. Abdelmoniem","orcid":"https://orcid.org/0000-0002-1374-1882"},"institutions":[{"id":"https://openalex.org/I166337079","display_name":"Queen Mary University of London","ror":"https://ror.org/026zzn846","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I166337079"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Ahmed M. Abdelmoniem","raw_affiliation_strings":["Queen Mary University of London, United Kingdom"],"affiliations":[{"raw_affiliation_string":"Queen Mary University of London, United Kingdom","institution_ids":["https://openalex.org/I166337079"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029466021","display_name":"Chen-Yu Ho","orcid":"https://orcid.org/0000-0001-6450-0280"},"institutions":[{"id":"https://openalex.org/I71920554","display_name":"King Abdullah University of Science and Technology","ror":"https://ror.org/01q3tbs38","country_code":"SA","type":"education","lineage":["https://openalex.org/I71920554"]}],"countries":["SA"],"is_corresponding":false,"raw_author_name":"Chen-Yu Ho","raw_affiliation_strings":["KAUST, Saudi Arabia"],"affiliations":[{"raw_affiliation_string":"KAUST, Saudi Arabia","institution_ids":["https://openalex.org/I71920554"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076154269","display_name":"Pantelis Papageorgiou","orcid":null},"institutions":[{"id":"https://openalex.org/I71920554","display_name":"King Abdullah University of Science and Technology","ror":"https://ror.org/01q3tbs38","country_code":"SA","type":"education","lineage":["https://openalex.org/I71920554"]}],"countries":["SA"],"is_corresponding":false,"raw_author_name":"Pantelis Papageorgiou","raw_affiliation_strings":["KAUST, Saudi Arabia"],"affiliations":[{"raw_affiliation_string":"KAUST, Saudi Arabia","institution_ids":["https://openalex.org/I71920554"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5042255975","display_name":"Marco Canini","orcid":"https://orcid.org/0000-0002-5051-4283"},"institutions":[{"id":"https://openalex.org/I71920554","display_name":"King Abdullah University of Science and Technology","ror":"https://ror.org/01q3tbs38","country_code":"SA","type":"education","lineage":["https://openalex.org/I71920554"]}],"countries":["SA"],"is_corresponding":false,"raw_author_name":"Marco Canini","raw_affiliation_strings":["KAUST, Saudi Arabia"],"affiliations":[{"raw_affiliation_string":"KAUST, Saudi Arabia","institution_ids":["https://openalex.org/I71920554"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5070017771"],"corresponding_institution_ids":["https://openalex.org/I166337079"],"apc_list":null,"apc_paid":null,"fwci":3.8639,"has_fulltext":true,"cited_by_count":28,"citation_normalized_percentile":{"value":0.9410324,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"9"},"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/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.9837999939918518,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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":0.9779000282287598,"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":0.8111311197280884},{"id":"https://openalex.org/keywords/software-deployment","display_name":"Software deployment","score":0.70673668384552},{"id":"https://openalex.org/keywords/federated-learning","display_name":"Federated learning","score":0.5918927788734436},{"id":"https://openalex.org/keywords/empirical-research","display_name":"Empirical research","score":0.49562108516693115},{"id":"https://openalex.org/keywords/server","display_name":"Server","score":0.472659707069397},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.3831841051578522},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.34305065870285034},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.33391547203063965},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.3152993321418762},{"id":"https://openalex.org/keywords/software-engineering","display_name":"Software engineering","score":0.15049687027931213}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8111311197280884},{"id":"https://openalex.org/C105339364","wikidata":"https://www.wikidata.org/wiki/Q2297740","display_name":"Software deployment","level":2,"score":0.70673668384552},{"id":"https://openalex.org/C2992525071","wikidata":"https://www.wikidata.org/wiki/Q50818671","display_name":"Federated learning","level":2,"score":0.5918927788734436},{"id":"https://openalex.org/C120936955","wikidata":"https://www.wikidata.org/wiki/Q2155640","display_name":"Empirical research","level":2,"score":0.49562108516693115},{"id":"https://openalex.org/C93996380","wikidata":"https://www.wikidata.org/wiki/Q44127","display_name":"Server","level":2,"score":0.472659707069397},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.3831841051578522},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.34305065870285034},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.33391547203063965},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.3152993321418762},{"id":"https://openalex.org/C115903868","wikidata":"https://www.wikidata.org/wiki/Q80993","display_name":"Software engineering","level":1,"score":0.15049687027931213},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1145/3517207.3526969","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3517207.3526969","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2nd European Workshop on Machine Learning and Systems","raw_type":"proceedings-article"},{"id":"pmh:oai:qmro.qmul.ac.uk:123456789/79664","is_oa":true,"landing_page_url":"https://qmro.qmul.ac.uk/xmlui/handle/123456789/79664","pdf_url":"https://qmro.qmul.ac.uk/xmlui/bitstream/123456789/79664/2/Mohamed%20Empirical%20analysis%20of%202022%20Accepted.pdf","source":{"id":"https://openalex.org/S4306400530","display_name":"Queen Mary Research Online (Queen Mary University of London)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I166337079","host_organization_name":"Queen Mary University of London","host_organization_lineage":["https://openalex.org/I166337079"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference Proceeding"},{"id":"pmh:oai:repository.kaust.edu.sa:10754/686311","is_oa":false,"landing_page_url":"http://hdl.handle.net/10754/686311","pdf_url":null,"source":{"id":"https://openalex.org/S4306401596","display_name":"King Abdullah University of Science and Technology Repository (King Abdullah University of Science and Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I71920554","host_organization_name":"King Abdullah University of Science and Technology","host_organization_lineage":["https://openalex.org/I71920554"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference Paper"}],"best_oa_location":{"id":"pmh:oai:qmro.qmul.ac.uk:123456789/79664","is_oa":true,"landing_page_url":"https://qmro.qmul.ac.uk/xmlui/handle/123456789/79664","pdf_url":"https://qmro.qmul.ac.uk/xmlui/bitstream/123456789/79664/2/Mohamed%20Empirical%20analysis%20of%202022%20Accepted.pdf","source":{"id":"https://openalex.org/S4306400530","display_name":"Queen Mary Research Online (Queen Mary University of London)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I166337079","host_organization_name":"Queen Mary University of London","host_organization_lineage":["https://openalex.org/I166337079"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference Proceeding"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4220934571.pdf","grobid_xml":"https://content.openalex.org/works/W4220934571.grobid-xml"},"referenced_works_count":19,"referenced_works":["https://openalex.org/W1834627138","https://openalex.org/W2057332538","https://openalex.org/W2473418344","https://openalex.org/W2612026221","https://openalex.org/W2767079719","https://openalex.org/W2775776326","https://openalex.org/W2798720628","https://openalex.org/W2912213068","https://openalex.org/W2930926105","https://openalex.org/W2975712713","https://openalex.org/W2998045710","https://openalex.org/W3010479380","https://openalex.org/W3014718068","https://openalex.org/W3021654819","https://openalex.org/W3045611708","https://openalex.org/W3103245149","https://openalex.org/W3105122387","https://openalex.org/W3107965923","https://openalex.org/W3154608090"],"related_works":["https://openalex.org/W96612179","https://openalex.org/W2566006169","https://openalex.org/W2770234245","https://openalex.org/W2987774938","https://openalex.org/W632915154","https://openalex.org/W4229499248","https://openalex.org/W4378874356","https://openalex.org/W2055733372","https://openalex.org/W2369811061","https://openalex.org/W3089997100"],"abstract_inverted_index":{"Federated":[0],"learning":[1,10],"(FL)":[2],"is":[3],"becoming":[4],"a":[5,79,121],"popular":[6,109],"paradigm":[7],"for":[8],"collaborative":[9],"over":[11,54],"distributed,":[12],"private":[13],"datasets":[14],"owned":[15],"by":[16,73],"non-trusting":[17],"entities.":[18],"FL":[19,46,70,110,140],"has":[20,29],"seen":[21],"successful":[22],"deployment":[23],"in":[24,32,139],"production":[25],"environments,":[26],"and":[27,41,59,88,128],"it":[28],"been":[30],"adopted":[31],"services":[33],"such":[34],"as":[35],"virtual":[36],"keyboards,":[37],"auto-completion,":[38],"item":[39],"recommendation,":[40],"several":[42],"IoT":[43],"applications.":[44],"However,":[45],"comes":[47],"with":[48],"the":[49,65,68,84,92,134],"challenge":[50],"of":[51,64,67,86,118,136],"performing":[52],"training":[53],"largely":[55],"heterogeneous":[56],"datasets,":[57],"devices,":[58],"networks":[60],"that":[61,115],"are":[62],"out":[63],"control":[66],"centralized":[69],"server.":[71],"Motivated":[72],"this":[74],"inherent":[75],"setting,":[76],"we":[77],"make":[78],"first":[80],"step":[81],"towards":[82],"characterizing":[83],"impact":[85,123],"device":[87],"behavioral":[89],"heterogeneity":[90,119,138],"on":[91,107,124,133],"trained":[93],"model.":[94],"We":[95],"conduct":[96],"an":[97],"extensive":[98],"empirical":[99],"study":[100],"spanning":[101],"close":[102],"to":[103],"1.5K":[104],"unique":[105],"configurations":[106],"five":[108],"benchmarks.":[111],"Our":[112],"analysis":[113],"shows":[114],"these":[116],"sources":[117],"have":[120],"major":[122],"both":[125],"model":[126],"performance":[127],"fairness,":[129],"thus":[130],"shedding":[131],"light":[132],"importance":[135],"considering":[137],"system":[141],"design.":[142]},"counts_by_year":[{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":11},{"year":2022,"cited_by_count":3}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}