{"id":"https://openalex.org/W3175268926","doi":"https://doi.org/10.1109/aicas51828.2021.9458526","title":"FL-HDC: Hyperdimensional Computing Design for the Application of Federated Learning","display_name":"FL-HDC: Hyperdimensional Computing Design for the Application of Federated Learning","publication_year":2021,"publication_date":"2021-06-06","ids":{"openalex":"https://openalex.org/W3175268926","doi":"https://doi.org/10.1109/aicas51828.2021.9458526","mag":"3175268926"},"language":"en","primary_location":{"id":"doi:10.1109/aicas51828.2021.9458526","is_oa":false,"landing_page_url":"https://doi.org/10.1109/aicas51828.2021.9458526","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE 3rd International Conference on Artificial Intelligence Circuits and Systems (AICAS)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5043096272","display_name":"Cheng-Yen Hsieh","orcid":null},"institutions":[{"id":"https://openalex.org/I16733864","display_name":"National Taiwan University","ror":"https://ror.org/05bqach95","country_code":"TW","type":"education","lineage":["https://openalex.org/I16733864"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Cheng-Yen Hsieh","raw_affiliation_strings":["National Taiwan University, Taipei, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Taiwan University, Taipei, Taiwan","institution_ids":["https://openalex.org/I16733864"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069905671","display_name":"Yu-Chuan Chuang","orcid":null},"institutions":[{"id":"https://openalex.org/I16733864","display_name":"National Taiwan University","ror":"https://ror.org/05bqach95","country_code":"TW","type":"education","lineage":["https://openalex.org/I16733864"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Yu-Chuan Chuang","raw_affiliation_strings":["Graduate Institute of Electronics Engineering, National Taiwan University, Taipei, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate Institute of Electronics Engineering, National Taiwan University, Taipei, Taiwan","institution_ids":["https://openalex.org/I16733864"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5109465340","display_name":"An-Yeu Wu","orcid":"https://orcid.org/0000-0003-4731-8633"},"institutions":[{"id":"https://openalex.org/I16733864","display_name":"National Taiwan University","ror":"https://ror.org/05bqach95","country_code":"TW","type":"education","lineage":["https://openalex.org/I16733864"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"An-Yeu Andy Wu","raw_affiliation_strings":["Graduate Institute of Electronics Engineering, National Taiwan University, Taipei, Taiwan","National Taiwan University, Taipei, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate Institute of Electronics Engineering, National Taiwan University, Taipei, Taiwan","institution_ids":["https://openalex.org/I16733864"]},{"raw_affiliation_string":"National Taiwan University, Taipei, Taiwan","institution_ids":["https://openalex.org/I16733864"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I16733864"],"apc_list":null,"apc_paid":null,"fwci":6.9134,"has_fulltext":false,"cited_by_count":28,"citation_normalized_percentile":{"value":0.98292718,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"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/T12808","display_name":"Ferroelectric and Negative Capacitance Devices","score":0.9998000264167786,"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":0.9998000264167786,"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/T11612","display_name":"Stochastic Gradient Optimization Techniques","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/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9926999807357788,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/mnist-database","display_name":"MNIST database","score":0.8975474834442139},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8022160530090332},{"id":"https://openalex.org/keywords/cloud-computing","display_name":"Cloud computing","score":0.6391971111297607},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.5907611846923828},{"id":"https://openalex.org/keywords/edge-device","display_name":"Edge device","score":0.5878793001174927},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5589425563812256},{"id":"https://openalex.org/keywords/upload","display_name":"Upload","score":0.5557632446289062},{"id":"https://openalex.org/keywords/edge-computing","display_name":"Edge computing","score":0.5438478589057922},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.5073437094688416},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5030271410942078},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.37407076358795166},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.354384183883667},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.12865665555000305},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.09612992405891418}],"concepts":[{"id":"https://openalex.org/C190502265","wikidata":"https://www.wikidata.org/wiki/Q17069496","display_name":"MNIST database","level":3,"score":0.8975474834442139},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8022160530090332},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.6391971111297607},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.5907611846923828},{"id":"https://openalex.org/C138236772","wikidata":"https://www.wikidata.org/wiki/Q25098575","display_name":"Edge device","level":3,"score":0.5878793001174927},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5589425563812256},{"id":"https://openalex.org/C71901391","wikidata":"https://www.wikidata.org/wiki/Q7126699","display_name":"Upload","level":2,"score":0.5557632446289062},{"id":"https://openalex.org/C2778456923","wikidata":"https://www.wikidata.org/wiki/Q5337692","display_name":"Edge computing","level":3,"score":0.5438478589057922},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.5073437094688416},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5030271410942078},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.37407076358795166},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.354384183883667},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.12865665555000305},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.09612992405891418}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/aicas51828.2021.9458526","is_oa":false,"landing_page_url":"https://doi.org/10.1109/aicas51828.2021.9458526","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE 3rd International Conference on Artificial Intelligence Circuits and Systems (AICAS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8700000047683716,"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320309618","display_name":"Ministry of Science and Technology","ror":"https://ror.org/02b207r52"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W2112796928","https://openalex.org/W2554538030","https://openalex.org/W2736172195","https://openalex.org/W2797218224","https://openalex.org/W2895910969","https://openalex.org/W2970402754","https://openalex.org/W2993412634","https://openalex.org/W3038077200","https://openalex.org/W3087790930","https://openalex.org/W4318619660","https://openalex.org/W6728757088","https://openalex.org/W6767022511"],"related_works":["https://openalex.org/W3116709161","https://openalex.org/W4322761281","https://openalex.org/W4238233472","https://openalex.org/W3166492421","https://openalex.org/W4313463218","https://openalex.org/W4312996489","https://openalex.org/W3111395152","https://openalex.org/W4313526662","https://openalex.org/W3106131444","https://openalex.org/W3216099748"],"abstract_inverted_index":{"Federated":[0],"learning":[1,6,76,105],"(FL)":[2],"is":[3,91],"a":[4,11,74,92,100],"privacy-preserving":[5],"framework,":[7],"which":[8,90],"collaboratively":[9],"learns":[10],"centralized":[12],"model":[13,22,30,83,144],"across":[14,130],"edge":[15,56],"devices.":[16,57],"Each":[17],"device":[18],"trains":[19],"an":[20],"independent":[21],"with":[23,103,137,157],"its":[24],"local":[25],"dataset":[26],"and":[27,134,153,162],"only":[28],"uploads":[29],"parameters":[31,84,145],"to":[32,72,85,107,146],"mitigate":[33],"privacy":[34],"concerns.":[35],"However,":[36],"most":[37],"FL":[38,50,118],"works":[39],"focus":[40],"on":[41,54],"deep":[42],"neural":[43],"networks":[44],"(DNNs),":[45],"whose":[46],"intensive":[47],"computation":[48],"hinders":[49],"from":[51],"practical":[52],"realization":[53],"resource-limited":[55],"In":[58,79],"this":[59],"paper,":[60],"we":[61,81,98],"exploit":[62],"the":[63,110,117,124,138,147],"high":[64],"energy":[65],"efficiency":[66],"properties":[67],"of":[68,126],"hyperdimensional":[69],"computing":[70],"(HDC)":[71],"propose":[73,99],"federated":[75],"HDC":[77],"(FL-HDC).":[78],"FL-HDC,":[80],"bipolarize":[82],"significantly":[86],"reduce":[87],"communication":[88,155],"costs,":[89],"primary":[93],"concern":[94],"in":[95,160],"FL.":[96],"Moreover,":[97],"retraining":[101],"mechanism":[102],"adaptive":[104],"rates":[106],"compensate":[108],"for":[109],"accuracy":[111,159],"degradation":[112],"caused":[113],"by":[114],"bipolarization.":[115],"Under":[116],"scenario,":[119],"our":[120,127],"simulation":[121],"results":[122],"show":[123],"effectiveness":[125],"proposed":[128],"FL-HDC":[129,149],"two":[131],"datasets,":[132],"MNIST":[133],"ISOLET.":[135],"Compared":[136],"previous":[139],"work":[140],"that":[141],"transmits":[142],"complete":[143],"cloud,":[148],"greatly":[150],"reduces":[151],"23x":[152],"9x":[154],"costs":[156],"comparable":[158],"ISOLET":[161],"MNIST,":[163],"respectively.":[164]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":4}],"updated_date":"2026-08-11T07:18:39.950985","created_date":"2025-10-10T00:00:00"}
