{"id":"https://openalex.org/W3211781253","doi":"https://doi.org/10.1145/3485730.3485946","title":"FedDL","display_name":"FedDL","publication_year":2021,"publication_date":"2021-11-11","ids":{"openalex":"https://openalex.org/W3211781253","doi":"https://doi.org/10.1145/3485730.3485946","mag":"3211781253"},"language":"en","primary_location":{"id":"doi:10.1145/3485730.3485946","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3485730.3485946","pdf_url":null,"source":null,"license":"public-domain","license_id":"https://openalex.org/licenses/public-domain","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 19th ACM Conference on Embedded Networked Sensor Systems","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/A5082120743","display_name":"Linlin Tu","orcid":null},"institutions":[{"id":"https://openalex.org/I87216513","display_name":"Michigan State University","ror":"https://ror.org/05hs6h993","country_code":"US","type":"education","lineage":["https://openalex.org/I87216513"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Linlin Tu","raw_affiliation_strings":["Michigan State University, East Lansing, MI, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Michigan State University, East Lansing, MI, USA","institution_ids":["https://openalex.org/I87216513"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087839973","display_name":"Xiaomin Ouyang","orcid":"https://orcid.org/0000-0003-0710-0963"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"HK","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Xiaomin Ouyang","raw_affiliation_strings":["The Chinese University of Hong Kong, Hong Kong SAR, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Chinese University of Hong Kong, Hong Kong SAR, China","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047215778","display_name":"Jiayu Zhou","orcid":"https://orcid.org/0000-0003-4336-6777"},"institutions":[{"id":"https://openalex.org/I87216513","display_name":"Michigan State University","ror":"https://ror.org/05hs6h993","country_code":"US","type":"education","lineage":["https://openalex.org/I87216513"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jiayu Zhou","raw_affiliation_strings":["Michigan State University, East Lansing, MI, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Michigan State University, East Lansing, MI, USA","institution_ids":["https://openalex.org/I87216513"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072700532","display_name":"Yuze He","orcid":"https://orcid.org/0009-0005-1575-6112"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"HK","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Yuze He","raw_affiliation_strings":["The Chinese University of Hong Kong, Hong Kong SAR, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Chinese University of Hong Kong, Hong Kong SAR, China","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5072780737","display_name":"Guoliang Xing","orcid":"https://orcid.org/0000-0003-1772-7751"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"HK","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Guoliang Xing","raw_affiliation_strings":["The Chinese University of Hong Kong, Hong Kong SAR, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Chinese University of Hong Kong, Hong Kong SAR, China","institution_ids":["https://openalex.org/I177725633"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":83,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"15","last_page":"28"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9994000196456909,"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":0.9994000196456909,"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/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9934999942779541,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9904999732971191,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"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/computer-science","display_name":"Computer science","score":0.8702923059463501},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.696674644947052},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6194778084754944},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.5784593224525452},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5765103101730347},{"id":"https://openalex.org/keywords/raw-data","display_name":"Raw data","score":0.5291231870651245},{"id":"https://openalex.org/keywords/aggregate","display_name":"Aggregate (composite)","score":0.4856809079647064},{"id":"https://openalex.org/keywords/scheme","display_name":"Scheme (mathematics)","score":0.4681587219238281},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.43572425842285156},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4195675849914551},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4029672145843506},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.13329187035560608}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8702923059463501},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.696674644947052},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6194778084754944},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.5784593224525452},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5765103101730347},{"id":"https://openalex.org/C132964779","wikidata":"https://www.wikidata.org/wiki/Q2110223","display_name":"Raw data","level":2,"score":0.5291231870651245},{"id":"https://openalex.org/C4679612","wikidata":"https://www.wikidata.org/wiki/Q866298","display_name":"Aggregate (composite)","level":2,"score":0.4856809079647064},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.4681587219238281},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.43572425842285156},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4195675849914551},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4029672145843506},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.13329187035560608},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","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},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3485730.3485946","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3485730.3485946","pdf_url":null,"source":null,"license":"public-domain","license_id":"https://openalex.org/licenses/public-domain","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 19th ACM Conference on Embedded Networked Sensor Systems","raw_type":"proceedings-article"},{"id":"pmh:oai:repository.hkust.edu.hk:1783.1-141686","is_oa":false,"landing_page_url":"http://repository.hkust.edu.hk/ir/Record/1783.1-141686","pdf_url":null,"source":{"id":"https://openalex.org/S4306401796","display_name":"Rare & Special e-Zone (The Hong Kong 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/I200769079","host_organization_name":"Hong Kong University of Science and Technology","host_organization_lineage":["https://openalex.org/I200769079"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Conference paper"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Partnerships for the goals","score":0.5199999809265137,"id":"https://metadata.un.org/sdg/17"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":56,"referenced_works":["https://openalex.org/W134960717","https://openalex.org/W193814004","https://openalex.org/W1760020891","https://openalex.org/W1857382374","https://openalex.org/W1988539834","https://openalex.org/W1991770012","https://openalex.org/W1995529998","https://openalex.org/W2062950526","https://openalex.org/W2116225745","https://openalex.org/W2126868529","https://openalex.org/W2134670479","https://openalex.org/W2144752499","https://openalex.org/W2149933564","https://openalex.org/W2150882603","https://openalex.org/W2153732053","https://openalex.org/W2156767919","https://openalex.org/W2337546824","https://openalex.org/W2342792048","https://openalex.org/W2403816530","https://openalex.org/W2406566318","https://openalex.org/W2502226073","https://openalex.org/W2519804223","https://openalex.org/W2541884796","https://openalex.org/W2549401308","https://openalex.org/W2604630936","https://openalex.org/W2606060986","https://openalex.org/W2611650652","https://openalex.org/W2619606157","https://openalex.org/W2624871570","https://openalex.org/W2742912327","https://openalex.org/W2759690896","https://openalex.org/W2770265759","https://openalex.org/W2782853073","https://openalex.org/W2806874609","https://openalex.org/W2808870406","https://openalex.org/W2851629429","https://openalex.org/W2888680699","https://openalex.org/W2889945482","https://openalex.org/W2897132279","https://openalex.org/W2900594532","https://openalex.org/W2912213068","https://openalex.org/W2913340405","https://openalex.org/W2922569945","https://openalex.org/W2963300197","https://openalex.org/W2963877604","https://openalex.org/W2980701909","https://openalex.org/W2995191368","https://openalex.org/W3016632787","https://openalex.org/W3102330835","https://openalex.org/W3109228974","https://openalex.org/W3127512444","https://openalex.org/W3158169529","https://openalex.org/W3174401204","https://openalex.org/W3213827093","https://openalex.org/W4286825659","https://openalex.org/W6681414149"],"related_works":["https://openalex.org/W2389214306","https://openalex.org/W2965083567","https://openalex.org/W4235240664","https://openalex.org/W1838576100","https://openalex.org/W2095886385","https://openalex.org/W2889616422","https://openalex.org/W2089704382","https://openalex.org/W1983399550","https://openalex.org/W97075385","https://openalex.org/W4386582991"],"abstract_inverted_index":{"Deep":[0],"learning":[1,28,34,76],"has":[2,217],"been":[3],"increasingly":[4],"applied":[5],"to":[6,55,60,90,114],"improve":[7],"human":[8,16],"activity":[9],"recognition":[10],"(HAR)":[11],"accuracy":[12,187],"and":[13,87,119,152,163,198,220],"reduce":[14],"the":[15,32,61,83,108,116,135,142,205,209],"efforts":[17],"of":[18,35,64,185,211],"handcrafted":[19],"feature":[20],"extractions.":[21],"Federated":[22],"Learning":[23],"(FL)":[24],"is":[25],"an":[26,124],"emerging":[27],"paradigm":[29],"that":[30,80,106,176,215],"enables":[31],"collaborative":[33],"a":[36,73,101,155],"global":[37],"model":[38,112,186],"without":[39],"exposing":[40],"users'":[41,65,111],"raw":[42],"data.":[43,66],"However,":[44],"existing":[45],"FL":[46,181],"approaches":[47],"yield":[48],"unsatisfactory":[49],"HAR":[50,79],"performance":[51],"as":[52],"they":[53],"fail":[54],"dynamically":[56],"aggregate":[57],"models":[58,93,121,132],"according":[59],"statistical":[62],"diversity":[63],"In":[67],"this":[68],"paper,":[69],"we":[70,99,159],"propose":[71],"FedDL,":[72],"novel":[74],"federated":[75],"system":[77],"for":[78,94,225],"can":[81,222],"capture":[82],"underlying":[84],"user":[85],"relationships":[86],"apply":[88],"them":[89],"learn":[91],"personalized":[92],"different":[95,212],"users":[96,170],"dynamically.":[97],"Specifically,":[98],"design":[100],"dynamic":[102,136],"layer":[103],"sharing":[104,117,137],"scheme":[105],"learns":[107],"similarity":[109],"among":[110],"weights":[113],"form":[115],"structure":[118],"merges":[120,130],"accordingly":[122],"in":[123,171,183],"iterative,":[125],"bottom-up":[126],"layer-wise":[127],"manner.":[128],"FedDL":[129,151,177,216],"local":[131],"based":[133],"on":[134,208],"scheme,":[138],"significantly":[139],"speeding":[140],"up":[141],"convergence":[143],"while":[144],"maintaining":[145],"high":[146,218],"accuracy.":[147],"We":[148],"have":[149],"implemented":[150],"evaluated":[153],"using":[154,161],"new":[156],"data":[157],"set":[158],"collected":[160],"LiDAR":[162],"four":[164],"public":[165],"real-world":[166,227],"datasets":[167,210],"involving":[168],"178":[169],"total.":[172],"The":[173],"results":[174,207],"show":[175,214],"outperforms":[178],"several":[179],"state-of-the-art":[180],"paradigms":[182],"terms":[184],"(by":[188,194],"more":[189,195],"than":[190,196],"15%),":[191],"converging":[192],"rate":[193],"70%),":[197],"communication":[199],"overhead":[200],"(about":[201],"30%":[202],"reduction).":[203],"Moreover,":[204],"testing":[206],"scales":[213],"scalability":[219],"hence":[221],"be":[223],"deployed":[224],"large-scale":[226],"applications.":[228]},"counts_by_year":[{"year":2026,"cited_by_count":7},{"year":2025,"cited_by_count":20},{"year":2024,"cited_by_count":19},{"year":2023,"cited_by_count":24},{"year":2022,"cited_by_count":13}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2021-11-22T00:00:00"}
