{"id":"https://openalex.org/W4415883017","doi":"https://doi.org/10.1109/twc.2025.3625961","title":"LoLaFL: Low-Latency Federated Learning via Forward-Only Propagation","display_name":"LoLaFL: Low-Latency Federated Learning via Forward-Only Propagation","publication_year":2025,"publication_date":"2025-11-04","ids":{"openalex":"https://openalex.org/W4415883017","doi":"https://doi.org/10.1109/twc.2025.3625961"},"language":null,"primary_location":{"id":"doi:10.1109/twc.2025.3625961","is_oa":false,"landing_page_url":"https://doi.org/10.1109/twc.2025.3625961","pdf_url":null,"source":{"id":"https://openalex.org/S63459445","display_name":"IEEE Transactions on Wireless Communications","issn_l":"1536-1276","issn":["1536-1276","1558-2248"],"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 Wireless Communications","raw_type":"journal-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/A5005654181","display_name":"Jierui Zhang","orcid":"https://orcid.org/0009-0002-0869-5305"},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Jierui Zhang","raw_affiliation_strings":["Department of Electrical and Electronic Engineering, The University of Hong Kong, Pokfulam, Hong Kong","Department of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong, China"],"raw_orcid":"https://orcid.org/0009-0002-0869-5305","affiliations":[{"raw_affiliation_string":"Department of Electrical and Electronic Engineering, The University of Hong Kong, Pokfulam, Hong Kong","institution_ids":["https://openalex.org/I889458895"]},{"raw_affiliation_string":"Department of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong, China","institution_ids":["https://openalex.org/I889458895"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069113085","display_name":"Jianhao Huang","orcid":"https://orcid.org/0000-0003-1490-2390"},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Jianhao Huang","raw_affiliation_strings":["Department of Electrical and Electronic Engineering, The University of Hong Kong, Pokfulam, Hong Kong","Department of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong, China"],"raw_orcid":"https://orcid.org/0000-0003-1490-2390","affiliations":[{"raw_affiliation_string":"Department of Electrical and Electronic Engineering, The University of Hong Kong, Pokfulam, Hong Kong","institution_ids":["https://openalex.org/I889458895"]},{"raw_affiliation_string":"Department of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong, China","institution_ids":["https://openalex.org/I889458895"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5007131492","display_name":"Kaibin Huang","orcid":"https://orcid.org/0000-0001-8773-4629"},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Kaibin Huang","raw_affiliation_strings":["Department of Electrical and Electronic Engineering, The University of Hong Kong, Pokfulam, Hong Kong","Department of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong, China"],"raw_orcid":"https://orcid.org/0000-0001-8773-4629","affiliations":[{"raw_affiliation_string":"Department of Electrical and Electronic Engineering, The University of Hong Kong, Pokfulam, Hong Kong","institution_ids":["https://openalex.org/I889458895"]},{"raw_affiliation_string":"Department of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong, China","institution_ids":["https://openalex.org/I889458895"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I889458895"],"apc_list":null,"apc_paid":null,"fwci":1.396,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.86825512,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"25","issue":null,"first_page":"6617","last_page":"6632"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.847599983215332,"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":0.847599983215332,"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/T13918","display_name":"Advanced Data and IoT Technologies","score":0.0215000007301569,"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"}},{"id":"https://openalex.org/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.008899999782443047,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/randomness","display_name":"Randomness","score":0.640999972820282},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5044000148773193},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.48989999294281006},{"id":"https://openalex.org/keywords/backpropagation","display_name":"Backpropagation","score":0.4880000054836273},{"id":"https://openalex.org/keywords/distributed-learning","display_name":"Distributed learning","score":0.4781999886035919},{"id":"https://openalex.org/keywords/data-aggregator","display_name":"Data aggregator","score":0.4334999918937683},{"id":"https://openalex.org/keywords/edge-device","display_name":"Edge device","score":0.4262999892234802},{"id":"https://openalex.org/keywords/latency","display_name":"Latency (audio)","score":0.4081999957561493},{"id":"https://openalex.org/keywords/supervised-learning","display_name":"Supervised learning","score":0.37599998712539673},{"id":"https://openalex.org/keywords/scheme","display_name":"Scheme (mathematics)","score":0.37220001220703125}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8689000010490417},{"id":"https://openalex.org/C125112378","wikidata":"https://www.wikidata.org/wiki/Q176640","display_name":"Randomness","level":2,"score":0.640999972820282},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5044000148773193},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.48989999294281006},{"id":"https://openalex.org/C155032097","wikidata":"https://www.wikidata.org/wiki/Q798503","display_name":"Backpropagation","level":3,"score":0.4880000054836273},{"id":"https://openalex.org/C2779582901","wikidata":"https://www.wikidata.org/wiki/Q21013010","display_name":"Distributed learning","level":2,"score":0.4781999886035919},{"id":"https://openalex.org/C82578977","wikidata":"https://www.wikidata.org/wiki/Q16773055","display_name":"Data aggregator","level":3,"score":0.4334999918937683},{"id":"https://openalex.org/C138236772","wikidata":"https://www.wikidata.org/wiki/Q25098575","display_name":"Edge device","level":3,"score":0.4262999892234802},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4253999888896942},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.4081999957561493},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.37599998712539673},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.37220001220703125},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.3718000054359436},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.36739999055862427},{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.36239999532699585},{"id":"https://openalex.org/C95491727","wikidata":"https://www.wikidata.org/wiki/Q992968","display_name":"Mobile telephony","level":3,"score":0.3582000136375427},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.3546999990940094},{"id":"https://openalex.org/C2779127903","wikidata":"https://www.wikidata.org/wiki/Q6510194","display_name":"Learning rule","level":3,"score":0.34139999747276306},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3386000096797943},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.33809998631477356},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.32710000872612},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.319599986076355},{"id":"https://openalex.org/C138293262","wikidata":"https://www.wikidata.org/wiki/Q1089578","display_name":"Linear network coding","level":3,"score":0.31470000743865967},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.3122999966144562},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.28610000014305115},{"id":"https://openalex.org/C153646914","wikidata":"https://www.wikidata.org/wiki/Q535695","display_name":"Cellular network","level":2,"score":0.2838999927043915},{"id":"https://openalex.org/C2992525071","wikidata":"https://www.wikidata.org/wiki/Q50818671","display_name":"Federated learning","level":2,"score":0.2759999930858612},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.2750999927520752},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.27480000257492065},{"id":"https://openalex.org/C557945733","wikidata":"https://www.wikidata.org/wiki/Q389772","display_name":"Data transmission","level":2,"score":0.2678000032901764},{"id":"https://openalex.org/C46637626","wikidata":"https://www.wikidata.org/wiki/Q6693015","display_name":"Low latency (capital markets)","level":2,"score":0.263700008392334},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.25450000166893005},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.2533000111579895},{"id":"https://openalex.org/C101765175","wikidata":"https://www.wikidata.org/wiki/Q577764","display_name":"Communications system","level":2,"score":0.2524999976158142}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/twc.2025.3625961","is_oa":false,"landing_page_url":"https://doi.org/10.1109/twc.2025.3625961","pdf_url":null,"source":{"id":"https://openalex.org/S63459445","display_name":"IEEE Transactions on Wireless Communications","issn_l":"1536-1276","issn":["1536-1276","1558-2248"],"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 Wireless Communications","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1346433516","display_name":null,"funder_award_id":"C1009-22G","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":47,"referenced_works":["https://openalex.org/W595252221","https://openalex.org/W1498436455","https://openalex.org/W1677182931","https://openalex.org/W2099111195","https://openalex.org/W2112796928","https://openalex.org/W2164931791","https://openalex.org/W2194775991","https://openalex.org/W2535690855","https://openalex.org/W2657631929","https://openalex.org/W2919115771","https://openalex.org/W2963250023","https://openalex.org/W2970408908","https://openalex.org/W2980191379","https://openalex.org/W2981096252","https://openalex.org/W2981138228","https://openalex.org/W2989289980","https://openalex.org/W2999074226","https://openalex.org/W3004277316","https://openalex.org/W3015636663","https://openalex.org/W3086073975","https://openalex.org/W3090615085","https://openalex.org/W3108590825","https://openalex.org/W3109847748","https://openalex.org/W3156448101","https://openalex.org/W3160246415","https://openalex.org/W3177095755","https://openalex.org/W3183240209","https://openalex.org/W3214521657","https://openalex.org/W4286242951","https://openalex.org/W4312258136","https://openalex.org/W4312340627","https://openalex.org/W4385834051","https://openalex.org/W4386320492","https://openalex.org/W4387042211","https://openalex.org/W4389981142","https://openalex.org/W4390204409","https://openalex.org/W4391248691","https://openalex.org/W4392251657","https://openalex.org/W4392251758","https://openalex.org/W4392901698","https://openalex.org/W4392939684","https://openalex.org/W4396878072","https://openalex.org/W4402742563","https://openalex.org/W4413120520","https://openalex.org/W4413267785","https://openalex.org/W4414405639","https://openalex.org/W7117157815"],"related_works":[],"abstract_inverted_index":{"Federated":[0,110],"learning":[1,13,37],"(FL)":[2],"has":[3],"emerged":[4],"as":[5],"a":[6],"widely":[7],"adopted":[8],"paradigm":[9],"for":[10,65,140,207],"enabling":[11],"edge":[12],"with":[14,25,122,199],"distributed":[15],"data":[16,19],"while":[17,220],"ensuring":[18],"privacy.":[20],"However,":[21],"the":[22,35,40,51,59,69,73,82,97,105,148,151,166,170,174,193,202],"traditional":[23,200],"FL":[24],"deep":[26],"neural":[27,100],"networks":[28],"trained":[29],"via":[30,113],"backpropagation":[31],"can":[32,209],"hardly":[33],"meet":[34],"low-latency":[36],"requirements":[38],"in":[39,156,212],"sixth":[41],"generation":[42],"(6G)":[43],"mobile":[44],"networks.":[45],"This":[46],"challenge":[47],"mainly":[48],"arises":[49],"from":[50],"high-dimensional":[52],"model":[53],"parameters":[54],"to":[55,68,90,180,191],"be":[56,159],"transmitted":[57],"and":[58,95,120,172,187,217],"numerous":[60],"rounds":[61],"of":[62,72,85,108,169,178,195,214],"communication":[63,125],"required":[64],"convergence":[66],"due":[67],"inherent":[70],"randomness":[71],"training":[74],"process.":[75],"To":[76],"address":[77],"this":[78],"issue,":[79],"we":[80,132],"adopt":[81],"state-of-the-art":[83],"principle":[84],"maximal":[86],"coding":[87],"rate":[88],"reduction":[89],"learn":[91],"linear":[92],"discriminative":[93],"features":[94,171,179],"extend":[96],"resultant":[98],"white-box":[99],"network":[101],"into":[102],"FL,":[103,201],"yielding":[104],"novel":[106],"framework":[107],"Low-Latency":[109],"Learning":[111],"(LoLaFL)":[112],"forward-only":[114],"propagation.":[115],"LoLaFL":[116,157,208],"enables":[117],"layer-wise":[118],"transmissions":[119],"aggregation":[121,138,155,205],"significantly":[123],"fewer":[124],"rounds,":[126],"thereby":[127],"considerably":[128],"reducing":[129],"latency.":[130],"Additionally,":[131],"propose":[133],"two":[134,203],"<italic":[135],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[136],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">nonlinear</i>":[137],"schemes":[139,206],"LoLaFL.":[141,196],"The":[142,161],"first":[143],"scheme":[144,163],"is":[145],"based":[146],"on":[147],"proof":[149],"that":[150],"optimal":[152],"NN":[153],"parameter":[154],"should":[158],"harmonic-mean-like.":[160],"second":[162],"further":[164],"exploits":[165],"low-rank":[167],"structures":[168],"transmits":[173],"low-rank-approximated":[175],"covariance":[176],"matrices":[177],"achieve":[181,210],"additional":[182],"latency":[183,213],"reduction.":[184],"Theoretic":[185],"analysis":[186],"experiments":[188],"are":[189],"conducted":[190],"evaluate":[192],"performance":[194],"In":[197],"comparison":[198],"nonlinear":[204],"reductions":[211],"over":[215],"87%":[216],"97%,":[218],"respectively,":[219],"maintaining":[221],"comparable":[222],"accuracies.":[223]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-01-11T23:08:45.486102","created_date":"2025-11-04T00:00:00"}
