{"id":"https://openalex.org/W3183351507","doi":"https://doi.org/10.23919/date51398.2021.9474218","title":"HyDREA: Towards More Robust and Efficient Machine Learning Systems with Hyperdimensional Computing","display_name":"HyDREA: Towards More Robust and Efficient Machine Learning Systems with Hyperdimensional Computing","publication_year":2021,"publication_date":"2021-02-01","ids":{"openalex":"https://openalex.org/W3183351507","doi":"https://doi.org/10.23919/date51398.2021.9474218","mag":"3183351507"},"language":"en","primary_location":{"id":"doi:10.23919/date51398.2021.9474218","is_oa":false,"landing_page_url":"https://doi.org/10.23919/date51398.2021.9474218","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 Design, Automation & Test in Europe Conference & Exhibition (DATE)","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/A5037764180","display_name":"Justin Morris","orcid":"https://orcid.org/0000-0002-7921-2561"},"institutions":[{"id":"https://openalex.org/I26538001","display_name":"San Diego State University","ror":"https://ror.org/0264fdx42","country_code":"US","type":"education","lineage":["https://openalex.org/I26538001"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Justin Morris","raw_affiliation_strings":["San Diego State University, San Diego, CA, USA"],"affiliations":[{"raw_affiliation_string":"San Diego State University, San Diego, CA, USA","institution_ids":["https://openalex.org/I26538001"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035400189","display_name":"Kazim Ergun","orcid":"https://orcid.org/0000-0002-5092-5074"},"institutions":[{"id":"https://openalex.org/I26538001","display_name":"San Diego State University","ror":"https://ror.org/0264fdx42","country_code":"US","type":"education","lineage":["https://openalex.org/I26538001"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kazim Ergun","raw_affiliation_strings":["San Diego State University, San Diego, CA, USA"],"affiliations":[{"raw_affiliation_string":"San Diego State University, San Diego, CA, USA","institution_ids":["https://openalex.org/I26538001"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060490428","display_name":"Behnam Khaleghi","orcid":"https://orcid.org/0000-0002-3655-0501"},"institutions":[{"id":"https://openalex.org/I36258959","display_name":"University of California, San Diego","ror":"https://ror.org/0168r3w48","country_code":"US","type":"education","lineage":["https://openalex.org/I36258959"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Behnam Khaleghi","raw_affiliation_strings":["University of California San Diego, La Jolla, CA, USA"],"affiliations":[{"raw_affiliation_string":"University of California San Diego, La Jolla, CA, USA","institution_ids":["https://openalex.org/I36258959"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033221192","display_name":"Mohsen Imani","orcid":"https://orcid.org/0000-0002-5761-0622"},"institutions":[{"id":"https://openalex.org/I204250578","display_name":"University of California, Irvine","ror":"https://ror.org/04gyf1771","country_code":"US","type":"education","lineage":["https://openalex.org/I204250578"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mohsen Imani","raw_affiliation_strings":["University of California Irvine, Irvine, CA, USA"],"affiliations":[{"raw_affiliation_string":"University of California Irvine, Irvine, CA, USA","institution_ids":["https://openalex.org/I204250578"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029850946","display_name":"Bar\u0131\u015f Ak\u015fanl\u0131","orcid":"https://orcid.org/0000-0001-6347-9061"},"institutions":[{"id":"https://openalex.org/I26538001","display_name":"San Diego State University","ror":"https://ror.org/0264fdx42","country_code":"US","type":"education","lineage":["https://openalex.org/I26538001"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Baris Aksanli","raw_affiliation_strings":["San Diego State University, San Diego, CA, USA"],"affiliations":[{"raw_affiliation_string":"San Diego State University, San Diego, CA, USA","institution_ids":["https://openalex.org/I26538001"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5025573294","display_name":"Tajana Rosing","orcid":"https://orcid.org/0000-0002-6954-997X"},"institutions":[{"id":"https://openalex.org/I36258959","display_name":"University of California, San Diego","ror":"https://ror.org/0168r3w48","country_code":"US","type":"education","lineage":["https://openalex.org/I36258959"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tajana Rosing","raw_affiliation_strings":["University of California San Diego, La Jolla, CA, USA"],"affiliations":[{"raw_affiliation_string":"University of California San Diego, La Jolla, CA, USA","institution_ids":["https://openalex.org/I36258959"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5037764180"],"corresponding_institution_ids":["https://openalex.org/I26538001"],"apc_list":null,"apc_paid":null,"fwci":1.3035,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":{"value":0.798373,"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":"723","last_page":"728"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12808","display_name":"Ferroelectric and Negative Capacitance Devices","score":1.0,"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":1.0,"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/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9970999956130981,"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/T12046","display_name":"MXene and MAX Phase Materials","score":0.9835000038146973,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials 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":0.8234724998474121},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.8099406957626343},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5344609022140503},{"id":"https://openalex.org/keywords/wireless","display_name":"Wireless","score":0.515381932258606},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4926913380622864},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.49060192704200745},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.48683661222457886},{"id":"https://openalex.org/keywords/cloud-computing","display_name":"Cloud computing","score":0.48586270213127136},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4775046706199646},{"id":"https://openalex.org/keywords/efficient-energy-use","display_name":"Efficient energy use","score":0.4706061780452728},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.4394184350967407},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.41206127405166626},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.3853301703929901},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.08388912677764893},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08385807275772095}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8234724998474121},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.8099406957626343},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5344609022140503},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.515381932258606},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4926913380622864},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.49060192704200745},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.48683661222457886},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.48586270213127136},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4775046706199646},{"id":"https://openalex.org/C2742236","wikidata":"https://www.wikidata.org/wiki/Q924713","display_name":"Efficient energy use","level":2,"score":0.4706061780452728},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.4394184350967407},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.41206127405166626},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.3853301703929901},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.08388912677764893},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08385807275772095},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","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},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.23919/date51398.2021.9474218","is_oa":false,"landing_page_url":"https://doi.org/10.23919/date51398.2021.9474218","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 Design, Automation & Test in Europe Conference & Exhibition (DATE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8999999761581421,"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W1576445103","https://openalex.org/W2070862086","https://openalex.org/W2476008461","https://openalex.org/W2518281301","https://openalex.org/W2535838896","https://openalex.org/W2583857261","https://openalex.org/W2613567208","https://openalex.org/W2771100829","https://openalex.org/W2809429070","https://openalex.org/W2895910969","https://openalex.org/W2900379535","https://openalex.org/W2915418849","https://openalex.org/W2945276917","https://openalex.org/W2949989598","https://openalex.org/W2990838824","https://openalex.org/W3017384461","https://openalex.org/W3041178375","https://openalex.org/W3046438704","https://openalex.org/W3090198137","https://openalex.org/W3103415979","https://openalex.org/W3138860252","https://openalex.org/W3158860039","https://openalex.org/W4232286453","https://openalex.org/W4243519499","https://openalex.org/W4297687186","https://openalex.org/W6752394539","https://openalex.org/W6762037011","https://openalex.org/W6780980396","https://openalex.org/W6792274978","https://openalex.org/W6794558526","https://openalex.org/W6825195337"],"related_works":["https://openalex.org/W4244478748","https://openalex.org/W4223488648","https://openalex.org/W2134969820","https://openalex.org/W2251605416","https://openalex.org/W4389340727","https://openalex.org/W4205786897","https://openalex.org/W3150465815","https://openalex.org/W1997222214","https://openalex.org/W4210772589","https://openalex.org/W4390846322"],"abstract_inverted_index":{"Today's":[0],"systems,":[1],"especially":[2],"in":[3,87,117,214],"the":[4,13,16,42,58,61,88,113,168,171,175,182,187,190,242],"age":[5],"of":[6,31,48,60,115,170,181,189,219],"federated":[7,119],"learning,":[8],"rely":[9],"on":[10,174],"sending":[11],"all":[12],"data":[14],"to":[15,36,56,71,85,151,177,185,227,241],"cloud,":[17],"and":[18,33,90,109,197,233],"then":[19],"use":[20],"complex":[21],"algorithms,":[22],"such":[23,82],"as":[24],"Deep":[25],"Neural":[26],"Networks,":[27],"which":[28],"require":[29],"billions":[30],"parameters":[32],"many":[34],"hours":[35],"train":[37],"a":[38,101,118,129,135,161],"model.":[39],"In":[40,95],"contrast,":[41],"human":[43,62],"brain":[44,63],"can":[45],"do":[46],"much":[47],"this":[49,96],"learning":[50,120],"effortlessly.":[51],"Hyperdimensional":[52],"(HD)":[53],"Computing":[54],"aims":[55],"mimic":[57],"behavior":[59],"by":[64,238],"utilizing":[65],"high":[66,195],"dimensional":[67],"representations.":[68],"This":[69],"leads":[70],"various":[72],"desirable":[73],"properties":[74],"that":[75,105,133,145,165,203],"other":[76,154],"Machine":[77],"Learning":[78],"(ML)":[79],"algorithms":[80],"lack":[81],"as:":[83],"robustness":[84,188],"noise":[86,152,178],"system":[89,104,206],"simple,":[91],"highly":[92],"parallel":[93],"operations.":[94],"paper,":[97],"we":[98,126],"propose":[99,160],"HyDREA,":[100],"HD":[102,191],"computing":[103],"is":[106,147,224],"Robust,":[107],"Efficient,":[108],"Accurate.":[110],"To":[111],"evaluate":[112],"feasibility":[114],"HyDREA":[116,146],"environment":[121,138],"with":[122,139,216],"wireless":[123,140],"communication":[124,141],"noise,":[125],"utilize":[127],"NS-3,":[128],"popular":[130],"network":[131],"simulator":[132],"models":[134],"real":[136],"world":[137],"noise.":[142],"We":[143,158],"found":[144],"48\u00d7":[148],"more":[149],"robust":[150],"than":[153,209],"comparable":[155],"ML":[156],"algorithms.":[157],"additionally":[159],"Processing-in-Memory":[162],"(PIM)":[163],"architecture":[164,223],"adaptively":[166],"changes":[167],"bitwidth":[169],"model":[172,192],"based":[173],"signal":[176],"ratio":[179],"(SNR)":[180],"incoming":[183],"sample":[184],"maintain":[186],"while":[193],"achieving":[194],"accuracy":[196],"energy":[198,231],"efficiency.":[199],"Our":[200,221],"results":[201],"indicate":[202],"our":[204],"proposed":[205],"loses":[207],"less":[208],"1%":[210],"classification":[211],"accuracy,":[212],"even":[213],"scenarios":[215],"an":[217],"SNR":[218],"6.64.":[220],"PIM":[222,244],"also":[225],"able":[226],"achieve":[228],"255\u00d7":[229],"better":[230],"efficiency":[232],"speed":[234],"up":[235],"execution":[236],"time":[237],"28\u00d7":[239],"compared":[240],"baseline":[243],"architecture.":[245]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}