{"id":"https://openalex.org/W4393168986","doi":"https://doi.org/10.1109/asp-dac58780.2024.10473907","title":"HyperFeel: An Efficient Federated Learning Framework Using Hyperdimensional Computing","display_name":"HyperFeel: An Efficient Federated Learning Framework Using Hyperdimensional Computing","publication_year":2024,"publication_date":"2024-01-22","ids":{"openalex":"https://openalex.org/W4393168986","doi":"https://doi.org/10.1109/asp-dac58780.2024.10473907"},"language":"en","primary_location":{"id":"doi:10.1109/asp-dac58780.2024.10473907","is_oa":false,"landing_page_url":"https://doi.org/10.1109/asp-dac58780.2024.10473907","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 29th Asia and South Pacific Design Automation Conference (ASP-DAC)","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/A5101399528","display_name":"Haoming Li","orcid":"https://orcid.org/0000-0002-2939-6534"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Haomin Li","raw_affiliation_strings":["Shanghai Jiao Tong University,China"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University,China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017670541","display_name":"Fangxin Liu","orcid":"https://orcid.org/0000-0002-8769-293X"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fangxin Liu","raw_affiliation_strings":["Shanghai Jiao Tong University,China"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University,China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101643092","display_name":"Yichi Chen","orcid":"https://orcid.org/0009-0002-8730-4172"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yichi Chen","raw_affiliation_strings":["Tianjin University,China"],"affiliations":[{"raw_affiliation_string":"Tianjin University,China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5053801300","display_name":"Li Jiang","orcid":"https://orcid.org/0000-0002-7353-8798"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Li Jiang","raw_affiliation_strings":["Shanghai Jiao Tong University,China"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University,China","institution_ids":["https://openalex.org/I183067930"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101399528"],"corresponding_institution_ids":["https://openalex.org/I183067930"],"apc_list":null,"apc_paid":null,"fwci":1.3347,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.79742415,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"716","last_page":"721"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12808","display_name":"Ferroelectric and Negative Capacitance Devices","score":0.9836999773979187,"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"}},"topics":[{"id":"https://openalex.org/T12808","display_name":"Ferroelectric and Negative Capacitance Devices","score":0.9836999773979187,"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/T10796","display_name":"Cooperative Communication and Network Coding","score":0.9380999803543091,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/computer-science","display_name":"Computer science","score":0.8120909929275513},{"id":"https://openalex.org/keywords/federated-learning","display_name":"Federated learning","score":0.4637715220451355},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.4397710859775543},{"id":"https://openalex.org/keywords/computer-architecture","display_name":"Computer architecture","score":0.3525267243385315},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.3303462862968445}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8120909929275513},{"id":"https://openalex.org/C2992525071","wikidata":"https://www.wikidata.org/wiki/Q50818671","display_name":"Federated learning","level":2,"score":0.4637715220451355},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.4397710859775543},{"id":"https://openalex.org/C118524514","wikidata":"https://www.wikidata.org/wiki/Q173212","display_name":"Computer architecture","level":1,"score":0.3525267243385315},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.3303462862968445}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/asp-dac58780.2024.10473907","is_oa":false,"landing_page_url":"https://doi.org/10.1109/asp-dac58780.2024.10473907","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 29th Asia and South Pacific Design Automation Conference (ASP-DAC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"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":36,"referenced_works":["https://openalex.org/W1510216169","https://openalex.org/W2085988980","https://openalex.org/W2491829854","https://openalex.org/W2554538030","https://openalex.org/W2590796488","https://openalex.org/W2606891064","https://openalex.org/W2771100829","https://openalex.org/W2912213068","https://openalex.org/W2946193510","https://openalex.org/W2955213239","https://openalex.org/W2989289980","https://openalex.org/W3006017224","https://openalex.org/W3021654819","https://openalex.org/W3101036738","https://openalex.org/W3142852780","https://openalex.org/W3158860039","https://openalex.org/W3175268926","https://openalex.org/W3187424755","https://openalex.org/W4213215092","https://openalex.org/W4281961012","https://openalex.org/W4284682915","https://openalex.org/W4289147229","https://openalex.org/W4293261883","https://openalex.org/W4318619660","https://openalex.org/W4386763504","https://openalex.org/W6723169266","https://openalex.org/W6728757088","https://openalex.org/W6748019269","https://openalex.org/W6756756286","https://openalex.org/W6759226220","https://openalex.org/W6760157594","https://openalex.org/W6762879059","https://openalex.org/W6765541894","https://openalex.org/W6772307254","https://openalex.org/W6778883912","https://openalex.org/W6792742759"],"related_works":["https://openalex.org/W2748952813","https://openalex.org/W4298221930","https://openalex.org/W2390279801","https://openalex.org/W2777914285","https://openalex.org/W2358668433","https://openalex.org/W4287823391","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W3013363440","https://openalex.org/W2382290278"],"abstract_inverted_index":{"Federated":[0,44],"Learning":[1,45],"(FL)":[2],"aims":[3],"to":[4,125,206,237],"establish":[5],"a":[6,116,159,178,211],"shared":[7,212],"model":[8,21,35,61],"across":[9],"decentralized":[10],"clients":[11],"under":[12],"the":[13,33,60,69,111,145,164,196,201,224],"privacy-preserving":[14],"constraint.":[15],"Each":[16],"client":[17,183],"learns":[18],"an":[19,78],"independent":[20],"with":[22,98,245],"local":[23,52],"data,":[24],"and":[25,127,133,140,168,235,251],"only":[26],"model\u2019s":[27],"updates":[28],"are":[29,46],"communicated.":[30],"However,":[31],"since":[32],"FL":[34,205,208,226],"typically":[36],"employs":[37],"computation-intensive":[38],"neural":[39,108],"networks,":[40],"major":[41],"challenges":[42],"in":[43,170],"(i)":[47],"significant":[48],"computation":[49],"overhead":[50,57],"for":[51,81,137,182],"training;":[53],"(ii)":[54],"massive":[55],"communication":[56,241],"arises":[58],"from":[59,203],"updates;":[62],"(iii)":[63],"notable":[64],"performance":[65,101],"degradation":[66],"caused":[67],"by":[68],"non-IID":[70,193],"scenario.":[71],"In":[72],"this":[73],"work,":[74],"we":[75,157,176,199],"propose":[76,158],"HyperFeel,":[77],"efficient":[79],"framework":[80,202],"federated":[82],"learning":[83,112],"based":[84,185,209],"on":[85,186,192,210,249],"Hyper-Dimensional":[86],"Computing":[87],"(HDC),":[88],"that":[89,106,219],"can":[90],"significantly":[91],"improve":[92],"communication/storage":[93],"efficiency":[94],"over":[95,243],"existing":[96],"works":[97],"nearly":[99],"no":[100],"degradation.":[102],"Unlike":[103],"current":[104],"solutions":[105],"employ":[107],"networks":[109],"as":[110],"models,":[113],"HyperFeel":[114,155,228],"introduces":[115],"simple":[117],"yet":[118],"effective":[119],"computing":[120],"paradigm":[121],"using":[122],"hyperdimensional":[123,150],"vectors":[124],"encode":[126],"represent":[128],"data.":[129,194],"It":[130],"performs":[131],"concise":[132],"highly":[134],"parallel":[135],"operations":[136],"encryption,":[138],"computation,":[139],"communication,":[141],"taking":[142],"advantage":[143],"of":[144,149,166],"lightweight":[146],"feature":[147],"representation":[148],"vectors.":[151],"To":[152],"further":[153],"enhance":[154],"performance,":[156],"two-fold":[160],"optimization":[161],"scheme":[162],"combining":[163],"characteristics":[165],"encoding":[167,213],"updating":[169],"hyper-dimensional":[171],"computing.":[172],"On":[173,195],"one":[174],"hand,":[175,198],"design":[177],"personalized":[179],"update":[180],"strategy":[181],"models":[184],"HDC,":[187],"which":[188],"achieves":[189,229],"better":[190],"accuracy":[191,247],"other":[197],"extend":[200],"horizontal":[204],"vertical":[207],"mechanism.":[214],"Comprehensive":[215],"experimental":[216],"results":[217],"demonstrate":[218],"our":[220],"method":[221],"consistently":[222],"outperforms":[223],"state-of-the-art":[225],"models.":[227],"$26":[230],"\\times":[231,239],"$":[232,240],"storage":[233],"reduction":[234,242],"up":[236],"$81":[238],"FedAvg,":[244],"minimal":[246],"drops":[248],"FEMNIST":[250],"Synthetic.":[252]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
