{"id":"https://openalex.org/W4416132318","doi":"https://doi.org/10.1109/ton.2026.3683538","title":"Communication-Efficient Adaptive Model-Driven Quantum Federated Learning","display_name":"Communication-Efficient Adaptive Model-Driven Quantum Federated Learning","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W4416132318","doi":"https://doi.org/10.1109/ton.2026.3683538"},"language":"en","primary_location":{"id":"doi:10.1109/ton.2026.3683538","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ton.2026.3683538","pdf_url":null,"source":{"id":"https://openalex.org/S5407042750","display_name":"IEEE Transactions on Networking","issn_l":"2998-4157","issn":["2998-4157"],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Networking","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2506.04548","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5049354375","display_name":"Dev Gurung","orcid":"https://orcid.org/0000-0001-7772-8049"},"institutions":[{"id":"https://openalex.org/I149704539","display_name":"Deakin University","ror":"https://ror.org/02czsnj07","country_code":"AU","type":"education","lineage":["https://openalex.org/I149704539"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Dev Gurung","raw_affiliation_strings":["School of IT, Deakin University, Burwood, VIC, Australia"],"raw_orcid":"https://orcid.org/0000-0001-7772-8049","affiliations":[{"raw_affiliation_string":"School of IT, Deakin University, Burwood, VIC, Australia","institution_ids":["https://openalex.org/I149704539"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038446422","display_name":"Shiva Raj Pokhrel","orcid":"https://orcid.org/0000-0001-5819-765X"},"institutions":[{"id":"https://openalex.org/I149704539","display_name":"Deakin University","ror":"https://ror.org/02czsnj07","country_code":"AU","type":"education","lineage":["https://openalex.org/I149704539"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Shiva Raj Pokhrel","raw_affiliation_strings":["School of IT, Deakin University, Burwood, VIC, Australia"],"raw_orcid":"https://orcid.org/0000-0001-5819-765X","affiliations":[{"raw_affiliation_string":"School of IT, Deakin University, Burwood, VIC, Australia","institution_ids":["https://openalex.org/I149704539"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I149704539"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.01767756,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"34","issue":null,"first_page":"4732","last_page":"4746"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10682","display_name":"Quantum Computing Algorithms and Architecture","score":0.6876999735832214,"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/T10682","display_name":"Quantum Computing Algorithms and Architecture","score":0.6876999735832214,"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/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.05920000001788139,"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/T10020","display_name":"Quantum Information and Cryptography","score":0.04309999942779541,"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/federated-learning","display_name":"Federated learning","score":0.7731999754905701},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.6036999821662903},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.4952999949455261},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.4885999858379364},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.3853999972343445}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8895000219345093},{"id":"https://openalex.org/C2992525071","wikidata":"https://www.wikidata.org/wiki/Q50818671","display_name":"Federated learning","level":2,"score":0.7731999754905701},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.6036999821662903},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.4952999949455261},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.4885999858379364},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.45829999446868896},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.40380001068115234},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.3853999972343445},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.287200003862381},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.28349998593330383},{"id":"https://openalex.org/C84114770","wikidata":"https://www.wikidata.org/wiki/Q46344","display_name":"Quantum","level":2,"score":0.2818000018596649},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.2687000036239624},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.25450000166893005}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/ton.2026.3683538","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ton.2026.3683538","pdf_url":null,"source":{"id":"https://openalex.org/S5407042750","display_name":"IEEE Transactions on Networking","issn_l":"2998-4157","issn":["2998-4157"],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Networking","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:2506.04548","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2506.04548","pdf_url":"https://arxiv.org/pdf/2506.04548","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2506.04548","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2506.04548","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"},{"id":"doi:10.26187/deakin.32038926","is_oa":true,"landing_page_url":"https://doi.org/10.26187/deakin.32038926","pdf_url":null,"source":{"id":"https://openalex.org/S4306402457","display_name":"Deakin Research Online (Deakin University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I149704539","host_organization_name":"Deakin University","host_organization_lineage":["https://openalex.org/I149704539"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"JournalArticle"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2506.04548","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2506.04548","pdf_url":"https://arxiv.org/pdf/2506.04548","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3718585410","display_name":null,"funder_award_id":"0000019042","funder_id":"https://openalex.org/F4320315885","funder_display_name":"Australian Government"}],"funders":[{"id":"https://openalex.org/F4320315885","display_name":"Australian Government","ror":"https://ror.org/0314h5y94"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4416132318.pdf","grobid_xml":"https://content.openalex.org/works/W4416132318.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Training":[0],"federated":[1,19],"learning":[2,20],"(FL)":[3],"at":[4],"scale":[5],"suffers":[6],"from":[7],"severe":[8],"communication":[9,35,85,101],"and":[10,38,44,52,70,80,100,107],"heterogeneity":[11],"constraints.":[12],"These":[13],"challenges":[14],"are":[15],"amplified":[16],"in":[17],"quantum":[18,81],"(QFL),":[21],"especially":[22],"under":[23,73],"non-IID":[24],"data.":[25],"We":[26,96],"propose":[27],"a":[28],"model-driven":[29],"QFL":[30,62,94],"(mdQFL)":[31],"framework":[32,48],"that":[33],"addresses":[34],"overhead,":[36],"scalability,":[37],"client":[39],"drift":[40],"through":[41],"adaptive":[42],"clustering":[43],"representative":[45],"aggregation.":[46],"The":[47],"enables":[49],"structured":[50],"personalization":[51],"efficient":[53],"update":[54],"compression":[55],"across":[56,77],"rounds.":[57],"mdQFL":[58],"is":[59],"the":[60],"first":[61],"approach":[63],"to":[64,104],"jointly":[65],"analyze":[66],"training":[67],"efficiency,":[68],"personalization,":[69],"test":[71],"generalization":[72],"heterogeneous":[74],"conditions.":[75],"Experiments":[76],"multiple":[78],"datasets":[79],"platforms":[82],"show":[83],"50%":[84],"reduction":[86],"while":[87],"maintaining":[88],"or":[89],"improving":[90],"accuracy":[91],"over":[92],"standard":[93],"base-lines.":[95],"provide":[97],"convergence":[98],"guarantees":[99],"complexity":[102],"bounds":[103],"establish":[105],"scalability":[106],"robustness.":[108]},"counts_by_year":[],"updated_date":"2026-04-23T06:14:38.165362","created_date":"2025-10-10T00:00:00"}