{"id":"https://openalex.org/W4413277770","doi":"https://doi.org/10.1109/tnnls.2025.3590015","title":"FedLSC: Improving Communication Efficiency and Robustness in Federated Learning With Stragglers and Adversaries","display_name":"FedLSC: Improving Communication Efficiency and Robustness in Federated Learning With Stragglers and Adversaries","publication_year":2025,"publication_date":"2025-08-18","ids":{"openalex":"https://openalex.org/W4413277770","doi":"https://doi.org/10.1109/tnnls.2025.3590015","pmid":"https://pubmed.ncbi.nlm.nih.gov/40824986"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2025.3590015","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2025.3590015","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5074784167","display_name":"Hyeong\u2010Gun Joo","orcid":"https://orcid.org/0009-0002-1828-6441"},"institutions":[{"id":"https://openalex.org/I4575257","display_name":"Hanyang University","ror":"https://ror.org/046865y68","country_code":"KR","type":"education","lineage":["https://openalex.org/I4575257"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Hyeong-Gun Joo","raw_affiliation_strings":["Department of Electronic Engineering, Hanyang University, Seoul, South Korea"],"raw_orcid":"https://orcid.org/0009-0002-1828-6441","affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Hanyang University, Seoul, South Korea","institution_ids":["https://openalex.org/I4575257"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084652371","display_name":"Song\u2010Nam Hong","orcid":"https://orcid.org/0000-0002-9535-2521"},"institutions":[{"id":"https://openalex.org/I4575257","display_name":"Hanyang University","ror":"https://ror.org/046865y68","country_code":"KR","type":"education","lineage":["https://openalex.org/I4575257"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Songnam Hong","raw_affiliation_strings":["Department of Electronic Engineering, Hanyang University, Seoul, South Korea"],"raw_orcid":"https://orcid.org/0000-0002-9535-2521","affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Hanyang University, Seoul, South Korea","institution_ids":["https://openalex.org/I4575257"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5003931214","display_name":"Dong\u2010Joon Shin","orcid":"https://orcid.org/0000-0002-5017-5314"},"institutions":[{"id":"https://openalex.org/I4575257","display_name":"Hanyang University","ror":"https://ror.org/046865y68","country_code":"KR","type":"education","lineage":["https://openalex.org/I4575257"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Dong-Joon Shin","raw_affiliation_strings":["Department of Electronic Engineering, Hanyang University, Seoul, South Korea"],"raw_orcid":"https://orcid.org/0000-0002-5017-5314","affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Hanyang University, Seoul, South Korea","institution_ids":["https://openalex.org/I4575257"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4575257"],"apc_list":null,"apc_paid":null,"fwci":2.792,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.91422222,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":"36","issue":"11","first_page":"19805","last_page":"19819"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.993399977684021,"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":0.993399977684021,"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":0.9169999957084656,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9154999852180481,"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/robustness","display_name":"Robustness (evolution)","score":0.6753310561180115},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6206083297729492},{"id":"https://openalex.org/keywords/chemistry","display_name":"Chemistry","score":0.10878238081932068}],"concepts":[{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6753310561180115},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6206083297729492},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.10878238081932068},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2025.3590015","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2025.3590015","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:40824986","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/40824986","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on neural networks and learning systems","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W2112796928","https://openalex.org/W2989289980","https://openalex.org/W3084357044","https://openalex.org/W3111009493","https://openalex.org/W3159481909","https://openalex.org/W3197519965","https://openalex.org/W3205368495","https://openalex.org/W3215194618","https://openalex.org/W4200234277","https://openalex.org/W4220779061","https://openalex.org/W4225014117","https://openalex.org/W4323644302","https://openalex.org/W4366463843","https://openalex.org/W4378697240","https://openalex.org/W4379805355","https://openalex.org/W4381855603","https://openalex.org/W4385338519","https://openalex.org/W4386869646","https://openalex.org/W4387872734","https://openalex.org/W4388952984","https://openalex.org/W4390603639","https://openalex.org/W4390826759","https://openalex.org/W4391095006","https://openalex.org/W4392939845"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"Despite":[0],"significant":[1,77,126],"progress":[2],"in":[3,61,153,176,183],"federated":[4],"learning":[5],"(FL),":[6],"persistent":[7],"challenges,":[8],"such":[9],"as":[10,147,149],"stragglers,":[11],"adversaries,":[12],"and":[13,37,59,83,107,112,128,134,173],"communication":[14,81,110,144],"costs":[15,82,145],"remain.":[16],"To":[17],"address":[18],"these":[19],"issues,":[20],"we":[21],"propose":[22],"FedLSC,":[23],"a":[24,97],"novel":[25],"FL":[26,164,185],"framework":[27],"that":[28,167],"leverages":[29],"layer-selected":[30],"correlation":[31],"(LSC)":[32],"to":[33,41,79,101,146],"enhance":[34],"both":[35],"robustness":[36,121],"efficiency.":[38],"In":[39],"contrast":[40],"the":[42,125,130,138],"existing":[43],"methods,":[44],"FedLSC":[45,64,142,168],"does":[46],"not":[47],"rely":[48],"on":[49],"public":[50],"data":[51],"during":[52],"model":[53,114],"training,":[54],"making":[55],"it":[56],"more":[57],"practical":[58],"resilient":[60],"real-world":[62],"scenarios.":[63],"introduces":[65],"three":[66],"key":[67],"innovations:":[68],"1)":[69],"preprocessing":[70],"of":[71,132,151],"layer":[72],"selection":[73],"(LS),":[74],"which":[75,119],"identifies":[76],"layers":[78,127],"reduce":[80,109],"performance":[84,103,172],"degradation;":[85],"2)":[86],"local":[87],"updates":[88],"using":[89],"LS-based":[90],"scaled":[91],"sign-stochastic":[92],"gradient":[93],"descent":[94],"(SSS),":[95],"introducing":[96],"layer-specific":[98],"scaling":[99],"mechanism":[100],"mitigate":[102],"loss":[104],"from":[105],"quantization":[106],"significantly":[108],"costs;":[111],"3)":[113],"aggregation":[115],"via":[116],"LSC-based":[117],"schemes,":[118],"enhances":[120],"by":[122],"processing":[123],"only":[124],"mitigating":[129],"impact":[131],"stragglers":[133],"adversaries.":[135],"Furthermore,":[136],"integrating":[137],"SSS":[139],"scheme":[140],"into":[141],"reduces":[143],"little":[148],"0.01%":[150],"those":[152],"state-of-the-art":[154],"(SOTA)":[155],"method":[156],"while":[157],"maintaining":[158],"performance.":[159],"Evaluations":[160],"conducted":[161],"across":[162],"various":[163],"scenarios":[165],"show":[166],"effectively":[169],"supports":[170],"robust":[171],"efficiency,":[174],"even":[175],"bandwidth-constrained":[177],"environments,":[178],"thereby":[179],"confirming":[180],"its":[181],"practicality":[182],"modern":[184],"applications.":[186]},"counts_by_year":[{"year":2026,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
