{"id":"https://openalex.org/W4412164290","doi":"https://doi.org/10.1109/memea65319.2025.11068095","title":"Preliminary Study of a Federated Learning Algorithm Based on an Evolutionary Random Subspace Forest","display_name":"Preliminary Study of a Federated Learning Algorithm Based on an Evolutionary Random Subspace Forest","publication_year":2025,"publication_date":"2025-05-28","ids":{"openalex":"https://openalex.org/W4412164290","doi":"https://doi.org/10.1109/memea65319.2025.11068095"},"language":"en","primary_location":{"id":"doi:10.1109/memea65319.2025.11068095","is_oa":false,"landing_page_url":"https://doi.org/10.1109/memea65319.2025.11068095","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE Medical Measurements & Applications (MeMeA)","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/A5118889323","display_name":"Thibo Van Doninck","orcid":null},"institutions":[{"id":"https://openalex.org/I4210112645","display_name":"Leefmilieu Brussel","ror":"https://ror.org/02dprkj51","country_code":"BE","type":"other","lineage":["https://openalex.org/I4210112645"]}],"countries":["BE"],"is_corresponding":true,"raw_author_name":"Thibo Van Doninck","raw_affiliation_strings":["BISI, VUB,Jette,Belgium"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"BISI, VUB,Jette,Belgium","institution_ids":["https://openalex.org/I4210112645"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5019777536","display_name":"Kurt Barb\u00e9","orcid":"https://orcid.org/0000-0002-7825-9077"},"institutions":[{"id":"https://openalex.org/I4210112645","display_name":"Leefmilieu Brussel","ror":"https://ror.org/02dprkj51","country_code":"BE","type":"other","lineage":["https://openalex.org/I4210112645"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Kurt Barb\u00e9","raw_affiliation_strings":["BISI, VUB,Jette,Belgium"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"BISI, VUB,Jette,Belgium","institution_ids":["https://openalex.org/I4210112645"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5118889323"],"corresponding_institution_ids":["https://openalex.org/I4210112645"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.07797902,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.949999988079071,"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/T10320","display_name":"Neural Networks and Applications","score":0.949999988079071,"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/T10057","display_name":"Face and Expression Recognition","score":0.9253000020980835,"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/T10100","display_name":"Metaheuristic Optimization Algorithms Research","score":0.9248999953269958,"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/random-forest","display_name":"Random forest","score":0.7523583173751831},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7260074615478516},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.717590868473053},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4827701151371002},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.34438058733940125},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.33829742670059204}],"concepts":[{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.7523583173751831},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7260074615478516},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.717590868473053},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4827701151371002},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.34438058733940125},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33829742670059204}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/memea65319.2025.11068095","is_oa":false,"landing_page_url":"https://doi.org/10.1109/memea65319.2025.11068095","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE Medical Measurements & Applications (MeMeA)","raw_type":"proceedings-article"},{"id":"pmh:oai:vubissmart:VUBISSMART:2000:249825","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4306402573","display_name":"VUBIR (Vrije Universiteit Brussel)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I13469542","host_organization_name":"Vrije Universiteit Brussel","host_organization_lineage":["https://openalex.org/I13469542"],"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":"article"},{"id":"pmh:oai:vubissmart:VUBISSMART:2000:260667","is_oa":false,"landing_page_url":"https://biblio.vub.ac.be/vubir/preliminary-study-of-a-federated-learning-algorithm-based-on-an-evolutionary-random-subspace-forest(b85442df-c9bb-4c7f-ac12-8f66b39f7b74).html","pdf_url":null,"source":{"id":"https://openalex.org/S4306402573","display_name":"VUBIR (Vrije Universiteit Brussel)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I13469542","host_organization_name":"Vrije Universiteit Brussel","host_organization_lineage":["https://openalex.org/I13469542"],"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":"article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Life in Land","score":0.550000011920929,"id":"https://metadata.un.org/sdg/15"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W1930624869","https://openalex.org/W2313339984","https://openalex.org/W2911964244","https://openalex.org/W3012501605","https://openalex.org/W3040685212","https://openalex.org/W4210284152","https://openalex.org/W4312258136","https://openalex.org/W4385225650","https://openalex.org/W4400520818","https://openalex.org/W6728757088"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4394984040","https://openalex.org/W4306674287","https://openalex.org/W4387369504","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W3107602296","https://openalex.org/W4364306694","https://openalex.org/W4312192474"],"abstract_inverted_index":{"Federated":[0],"learning":[1,24,38,88,150,190],"has":[2],"seen":[3,31,58],"a":[4,60,86,91,95,120,136,194],"rise":[5],"in":[6,33,63],"interest":[7],"given":[8],"that":[9,140],"privacy":[10],"concerns":[11],"of":[12,36,44,79,141,187],"contemporary":[13],"data":[14,17],"can":[15,56],"hinder":[16],"pooling.":[18],"To":[19],"this":[20,64],"end,":[21],"several":[22],"machine":[23],"algorithms":[25],"including":[26],"random":[27,46,52],"forests":[28,168],"have":[29],"already":[30],"use":[32],"some":[34],"kind":[35],"federated":[37,87,149,189],"setting.":[39],"A":[40,108],"recently":[41],"developed":[42],"variation":[43],"the":[45,50,77,80,112,129,148,167,174,185,188],"forest":[47,54,122],"algorithm,":[48],"called":[49],"evolutionary":[51],"subspace":[53],"(ERSF),":[55],"be":[57,83,178],"as":[59],"viable":[61],"candidate":[62],"field":[65],"due":[66],"to":[67,82,85,128,139,154,177,181],"its":[68],"highly":[69],"parallelizable":[70],"and":[71,103,192],"iterative":[72],"nature.":[73],"This":[74,183],"work":[75],"assessed":[76],"potential":[78],"ERSF":[81,143],"extended":[84],"algorithm":[89,151,176],"using":[90],"simulated":[92],"dataset":[93,100],"representing":[94],"regression":[96],"problem.":[97],"The":[98],"generated":[99],"was":[101,124,152],"split":[102],"distributed":[104],"amongst":[105],"different":[106],"nodes.":[107],"central":[109],"node":[110,118],"aggregated":[111],"locally":[113],"trained":[114,144,159,169],"ERSFs":[115],"from":[116],"each":[117,163],"into":[119],"global":[121],"which":[123,157],"sent":[125],"back":[126],"out":[127],"nodes":[130],"for":[131,197],"further":[132],"local":[133],"training.":[134],"With":[135],"performance":[137],"comparable":[138],"an":[142],"on":[145,162],"pooled":[146],"data,":[147],"able":[153],"outperform":[155],"ERSF's":[156],"were":[158],"fully":[160,170],"separate":[161,171],"node.":[164],"Comparison":[165],"with":[166],"also":[172],"showed":[173],"current":[175],"less":[179],"prone":[180],"overfitting.":[182],"reaffirms":[184],"advantages":[186],"paradigm":[191],"establishes":[193],"promising":[195],"framework":[196],"future":[198],"research.":[199]},"counts_by_year":[],"updated_date":"2026-04-26T08:31:28.666265","created_date":"2025-10-10T00:00:00"}