{"id":"https://openalex.org/W4390874733","doi":"https://doi.org/10.1109/icrc60800.2023.10386671","title":"RefineHD: Accurate and Efficient Single-Pass Adaptive Learning Using Hyperdimensional Computing","display_name":"RefineHD: Accurate and Efficient Single-Pass Adaptive Learning Using Hyperdimensional Computing","publication_year":2023,"publication_date":"2023-12-05","ids":{"openalex":"https://openalex.org/W4390874733","doi":"https://doi.org/10.1109/icrc60800.2023.10386671"},"language":"en","primary_location":{"id":"doi:10.1109/icrc60800.2023.10386671","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icrc60800.2023.10386671","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Rebooting Computing (ICRC)","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/A5013401821","display_name":"Pere Verg\u00e9s","orcid":null},"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":true,"raw_author_name":"Pere Verg\u00e9s","raw_affiliation_strings":["University of California, Irvine,Department of Computer Science,Irvine,California,United States of America","Department of Computer Science, University of California, Irvine, Irvine, California, United States of America"],"affiliations":[{"raw_affiliation_string":"University of California, Irvine,Department of Computer Science,Irvine,California,United States of America","institution_ids":["https://openalex.org/I204250578"]},{"raw_affiliation_string":"Department of Computer Science, University of California, Irvine, Irvine, California, United States of America","institution_ids":["https://openalex.org/I204250578"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019614336","display_name":"Tony Givargis","orcid":"https://orcid.org/0000-0002-1608-9324"},"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":"Tony Givargis","raw_affiliation_strings":["University of California, Irvine,Department of Computer Science,Irvine,California,United States of America","Department of Computer Science, University of California, Irvine, Irvine, California, United States of America"],"affiliations":[{"raw_affiliation_string":"University of California, Irvine,Department of Computer Science,Irvine,California,United States of America","institution_ids":["https://openalex.org/I204250578"]},{"raw_affiliation_string":"Department of Computer Science, University of California, Irvine, Irvine, California, United States of America","institution_ids":["https://openalex.org/I204250578"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102229114","display_name":"Alexandru Nicolau","orcid":null},"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":"Alexandru Nicolau","raw_affiliation_strings":["University of California, Irvine,Department of Computer Science,Irvine,California,United States of America","Department of Computer Science, University of California, Irvine, Irvine, California, United States of America"],"affiliations":[{"raw_affiliation_string":"University of California, Irvine,Department of Computer Science,Irvine,California,United States of America","institution_ids":["https://openalex.org/I204250578"]},{"raw_affiliation_string":"Department of Computer Science, University of California, Irvine, Irvine, California, United States of America","institution_ids":["https://openalex.org/I204250578"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5013401821"],"corresponding_institution_ids":["https://openalex.org/I204250578"],"apc_list":null,"apc_paid":null,"fwci":1.3156,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.80961643,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"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":0.9986000061035156,"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/T12611","display_name":"Neural Networks and Reservoir Computing","score":0.9961000084877014,"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/inference","display_name":"Inference","score":0.7626490592956543},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7479095458984375},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6881490349769592},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.48837965726852417},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.47200867533683777},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.42721492052078247},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.3364871144294739}],"concepts":[{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.7626490592956543},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7479095458984375},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6881490349769592},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48837965726852417},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.47200867533683777},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.42721492052078247},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.3364871144294739},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"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/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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icrc60800.2023.10386671","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icrc60800.2023.10386671","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Rebooting Computing (ICRC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W1573706465","https://openalex.org/W2001972101","https://openalex.org/W2026297770","https://openalex.org/W2070862086","https://openalex.org/W2119144962","https://openalex.org/W2141125852","https://openalex.org/W2476008461","https://openalex.org/W2554538030","https://openalex.org/W2586430547","https://openalex.org/W2762654171","https://openalex.org/W2771100829","https://openalex.org/W2793457039","https://openalex.org/W2884945696","https://openalex.org/W2943798647","https://openalex.org/W2963363970","https://openalex.org/W2973650171","https://openalex.org/W2993412634","https://openalex.org/W3000475177","https://openalex.org/W3019791076","https://openalex.org/W3021560762","https://openalex.org/W3036478084","https://openalex.org/W3105115497","https://openalex.org/W3107466412","https://openalex.org/W3118608800","https://openalex.org/W3126220825","https://openalex.org/W3168260338","https://openalex.org/W3175829250","https://openalex.org/W3184049905","https://openalex.org/W3193529729","https://openalex.org/W3204836041","https://openalex.org/W3208591904","https://openalex.org/W4205199576","https://openalex.org/W4212879565","https://openalex.org/W4280579492","https://openalex.org/W4294975513","https://openalex.org/W4367060497","https://openalex.org/W4386763951","https://openalex.org/W4387607842","https://openalex.org/W4388280142","https://openalex.org/W6636444753","https://openalex.org/W6796199476"],"related_works":["https://openalex.org/W2770593030","https://openalex.org/W2055243143","https://openalex.org/W3154990682","https://openalex.org/W2560201613","https://openalex.org/W2171975302","https://openalex.org/W2022352247","https://openalex.org/W2488129135","https://openalex.org/W4312219546","https://openalex.org/W2154044472","https://openalex.org/W4210772589"],"abstract_inverted_index":{"Hyperdimensional":[0],"computing":[1,5],"(HDC)":[2],"is":[3],"a":[4,132,151,162,170,179],"framework":[6],"that":[7,80],"has":[8],"gained":[9],"significant":[10],"attention":[11],"due":[12,64],"to":[13,65,86,120,141],"its":[14,28,142],"high":[15],"efficiency":[16,96],"and":[17,20,31,83,100,137],"rapid":[18],"training":[19,99],"inference":[21,32,189],"of":[22,68,108,156,165,182],"machine":[23],"learning":[24,30,48,78],"algorithms":[25],"[1].":[26],"With":[27],"fast":[29,46],"capabilities,":[33],"HDC":[34,43,90,143,176],"shows":[35],"excellent":[36],"potential":[37],"for":[38,45],"IoT/Embedded":[39],"systems.":[40],"However,":[41],"while":[42,92,185],"allows":[44],"single-pass":[47],"[2],":[49],"it":[50],"suffers":[51],"from":[52,57,126],"weak":[53],"classification":[54],"accuracy,":[55],"resulting":[56],"model":[58,134],"saturation":[59,109],"caused":[60],"by":[61,110],"excessive":[62],"noise":[63,136],"the":[66,87,94,106,121,127,175,187],"addition":[67],"similar":[69],"patterns.":[70],"In":[71],"this":[72,147],"paper,":[73],"we":[74,130,149,168],"propose":[75],"an":[76],"adaptive":[77,89],"method":[79,104],"surpasses":[81],"accuracy":[82,154],"robustness":[84],"compared":[85],"state-of-the-art":[88],"model,":[91],"maintaining":[93],"same":[95,188],"during":[97],"both":[98],"testing":[101],"phases.":[102],"Our":[103],"addresses":[105],"issue":[107],"selectively":[111],"adding":[112],"correctly":[113],"classified":[114],"samples":[115],"only":[116],"when":[117],"their":[118],"similarity":[119],"existing":[122],"patterns":[123],"sufficiently":[124],"differs":[125],"class.":[128],"Moreover,":[129],"achieve":[131,150],"robust":[133],"against":[135],"hardware":[138],"failures,":[139],"thanks":[140],"holographic":[144],"properties.":[145],"Through":[146],"approach,":[148],"remarkable":[152,171],"average":[153],"improvement":[155,164,173,181],"+2.8%":[157],"across":[158],"126":[159],"datasets":[160],"(with":[161,178],"maximum":[163,180],"+26%).":[166],"Furthermore,":[167],"observe":[169],"+6.6%":[172],"over":[174],"baseline":[177],"+67%),":[183],"all":[184],"retaining":[186],"efficiency.":[190]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":3}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}
