{"id":"https://openalex.org/W3112008082","doi":"https://doi.org/10.1109/tnnls.2020.3041677","title":"Mixed-Precision Kernel Recursive Least Squares","display_name":"Mixed-Precision Kernel Recursive Least Squares","publication_year":2020,"publication_date":"2020-12-17","ids":{"openalex":"https://openalex.org/W3112008082","doi":"https://doi.org/10.1109/tnnls.2020.3041677","mag":"3112008082","pmid":"https://pubmed.ncbi.nlm.nih.gov/33326387"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2020.3041677","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2020.3041677","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://pureadmin.qub.ac.uk/ws/files/225973925/FINAL_VERSION.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"JunKyu Lee","orcid":"https://orcid.org/0000-0003-1985-5116"},"institutions":[{"id":"https://openalex.org/I126231945","display_name":"Queen's University Belfast","ror":"https://ror.org/00hswnk62","country_code":"GB","type":"education","lineage":["https://openalex.org/I126231945"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"JunKyu Lee","raw_affiliation_strings":["Institute of Electronics, Communications and Information Technology (ECIT), Queen&#x2019;s University Belfast, Belfast, U.K"],"raw_orcid":"https://orcid.org/0000-0003-1985-5116","affiliations":[{"raw_affiliation_string":"Institute of Electronics, Communications and Information Technology (ECIT), Queen&#x2019;s University Belfast, Belfast, U.K","institution_ids":["https://openalex.org/I126231945"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Dimitrios S. Nikolopoulos","orcid":"https://orcid.org/0000-0003-0217-8307"},"institutions":[{"id":"https://openalex.org/I859038795","display_name":"Virginia Tech","ror":"https://ror.org/02smfhw86","country_code":"US","type":"education","lineage":["https://openalex.org/I859038795"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dimitrios S. Nikolopoulos","raw_affiliation_strings":["Virginia Tech, Blacksburg, VA, USA"],"raw_orcid":"https://orcid.org/0000-0003-0217-8307","affiliations":[{"raw_affiliation_string":"Virginia Tech, Blacksburg, VA, USA","institution_ids":["https://openalex.org/I859038795"]}]},{"author_position":"last","author":{"id":null,"display_name":"Hans Vandierendonck","orcid":"https://orcid.org/0000-0001-5868-9259"},"institutions":[{"id":"https://openalex.org/I126231945","display_name":"Queen's University Belfast","ror":"https://ror.org/00hswnk62","country_code":"GB","type":"education","lineage":["https://openalex.org/I126231945"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Hans Vandierendonck","raw_affiliation_strings":["Institute of Electronics, Communications and Information Technology (ECIT), Queen&#x2019;s University Belfast, Belfast, U.K"],"raw_orcid":"https://orcid.org/0000-0001-5868-9259","affiliations":[{"raw_affiliation_string":"Institute of Electronics, Communications and Information Technology (ECIT), Queen&#x2019;s University Belfast, Belfast, U.K","institution_ids":["https://openalex.org/I126231945"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.3238,"has_fulltext":true,"cited_by_count":7,"citation_normalized_percentile":{"value":0.64945047,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"33","issue":"3","first_page":"1284","last_page":"1298"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.21230000257492065,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.21230000257492065,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12611","display_name":"Neural Networks and Reservoir Computing","score":0.1615999937057495,"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/T11490","display_name":"Hydrological Forecasting Using AI","score":0.08009999990463257,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.6270999908447266},{"id":"https://openalex.org/keywords/chaotic","display_name":"Chaotic","score":0.5659000277519226},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.5636000037193298},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.4921000003814697},{"id":"https://openalex.org/keywords/memory-footprint","display_name":"Memory footprint","score":0.4706000089645386},{"id":"https://openalex.org/keywords/least-squares-function-approximation","display_name":"Least-squares function approximation","score":0.3817000091075897},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.34139999747276306}],"concepts":[{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.6270999908447266},{"id":"https://openalex.org/C2777052490","wikidata":"https://www.wikidata.org/wiki/Q5072826","display_name":"Chaotic","level":2,"score":0.5659000277519226},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.5636000037193298},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5558000206947327},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.4921000003814697},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4781000018119812},{"id":"https://openalex.org/C74912251","wikidata":"https://www.wikidata.org/wiki/Q6815727","display_name":"Memory footprint","level":2,"score":0.4706000089645386},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4016999900341034},{"id":"https://openalex.org/C9936470","wikidata":"https://www.wikidata.org/wiki/Q6510405","display_name":"Least-squares function approximation","level":3,"score":0.3817000091075897},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.34139999747276306},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.33799999952316284},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.3303999900817871},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.32850000262260437},{"id":"https://openalex.org/C145249878","wikidata":"https://www.wikidata.org/wiki/Q2835868","display_name":"Recursive least squares filter","level":3,"score":0.3188000023365021},{"id":"https://openalex.org/C157764524","wikidata":"https://www.wikidata.org/wiki/Q1383412","display_name":"Throughput","level":3,"score":0.3165999948978424},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.3091999888420105},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.2529999911785126},{"id":"https://openalex.org/C2987469083","wikidata":"https://www.wikidata.org/wiki/Q166314","display_name":"Chaotic systems","level":3,"score":0.2524000108242035},{"id":"https://openalex.org/C311688","wikidata":"https://www.wikidata.org/wiki/Q2393193","display_name":"Time complexity","level":2,"score":0.25099998712539673}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/tnnls.2020.3041677","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2020.3041677","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:33326387","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/33326387","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on neural networks and learning systems","raw_type":null},{"id":"pmh:oai:pure.qub.ac.uk/portal:openaire/2eb83186-6c67-4790-b885-f81eda7abdbc","is_oa":true,"landing_page_url":"https://pure.qub.ac.uk/en/publications/2eb83186-6c67-4790-b885-f81eda7abdbc","pdf_url":"https://pureadmin.qub.ac.uk/ws/files/225973925/FINAL_VERSION.pdf","source":{"id":"https://openalex.org/S4306402319","display_name":"Research Portal (Queen's University Belfast)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I126231945","host_organization_name":"Queen's University Belfast","host_organization_lineage":["https://openalex.org/I126231945"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Lee, J, Nikolopoulos, D S & Vandierendonck, H 2020, 'Mixed-Precision Kernel Recursive Least Squares', IEEE Transactions on Neural Networks and Learning Systems. https://doi.org/10.1109/TNNLS.2020.3041677","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"pmh:oai:pure.qub.ac.uk/portal:openaire/2eb83186-6c67-4790-b885-f81eda7abdbc","is_oa":true,"landing_page_url":"https://pure.qub.ac.uk/en/publications/2eb83186-6c67-4790-b885-f81eda7abdbc","pdf_url":"https://pureadmin.qub.ac.uk/ws/files/225973925/FINAL_VERSION.pdf","source":{"id":"https://openalex.org/S4306402319","display_name":"Research Portal (Queen's University Belfast)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I126231945","host_organization_name":"Queen's University Belfast","host_organization_lineage":["https://openalex.org/I126231945"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Lee, J, Nikolopoulos, D S & Vandierendonck, H 2020, 'Mixed-Precision Kernel Recursive Least Squares', IEEE Transactions on Neural Networks and Learning Systems. https://doi.org/10.1109/TNNLS.2020.3041677","raw_type":"info:eu-repo/semantics/article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1987947441","display_name":"Energy Efficient Transprecision Techniques for Linear Solver","funder_award_id":"798209","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"},{"id":"https://openalex.org/G2274311490","display_name":null,"funder_award_id":"732631 (OPRECOMP)","funder_id":"https://openalex.org/F4320338336","funder_display_name":"H2020 Future and Emerging Technologies"},{"id":"https://openalex.org/G3607539430","display_name":"Open transPREcision COMPuting","funder_award_id":"732631","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"},{"id":"https://openalex.org/G7091921714","display_name":null,"funder_award_id":"798209 (Entrans)","funder_id":"https://openalex.org/F4320338336","funder_display_name":"H2020 Future and Emerging Technologies"}],"funders":[{"id":"https://openalex.org/F4320320300","display_name":"European Commission","ror":"https://ror.org/00k4n6c32"},{"id":"https://openalex.org/F4320338336","display_name":"H2020 Future and Emerging Technologies","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3112008082.pdf","grobid_xml":"https://content.openalex.org/works/W3112008082.grobid-xml"},"referenced_works_count":35,"referenced_works":["https://openalex.org/W1560724230","https://openalex.org/W1968165559","https://openalex.org/W1973914465","https://openalex.org/W1987568357","https://openalex.org/W2011197824","https://openalex.org/W2031365860","https://openalex.org/W2069035017","https://openalex.org/W2076118331","https://openalex.org/W2078126355","https://openalex.org/W2094631910","https://openalex.org/W2105934661","https://openalex.org/W2109626466","https://openalex.org/W2114979199","https://openalex.org/W2115232518","https://openalex.org/W2122021878","https://openalex.org/W2127961257","https://openalex.org/W2134583708","https://openalex.org/W2138013597","https://openalex.org/W2139320579","https://openalex.org/W2153290280","https://openalex.org/W2169004268","https://openalex.org/W2204310803","https://openalex.org/W2259181503","https://openalex.org/W2481926318","https://openalex.org/W2563468918","https://openalex.org/W2734874104","https://openalex.org/W2779013372","https://openalex.org/W2788630562","https://openalex.org/W3125566411","https://openalex.org/W3150959508","https://openalex.org/W4205567043","https://openalex.org/W4292022450","https://openalex.org/W6638783484","https://openalex.org/W6675672627","https://openalex.org/W6745245109"],"related_works":[],"abstract_inverted_index":{"Kernel":[0],"recursive":[1],"least":[2],"squares":[3],"(KRLS)":[4],"is":[5],"a":[6,33,38,95,99,104,109,115],"widely":[7],"used":[8],"online":[9],"machine":[10],"learning":[11],"algorithm":[12],"for":[13,94],"time":[14,102,107,112,119],"series":[15],"predictions.":[16],"In":[17],"this":[18],"article,":[19],"we":[20],"present":[21],"the":[22,49,65],"mixed-precision":[23,43,62],"KRLS,":[24],"producing":[25],"equivalent":[26],"prediction":[27,88],"accuracy":[28,89],"to":[29,48,91],"double-precision":[30,92],"KRLS":[31,44,63,93],"with":[32],"higher":[34],"training":[35,72],"throughput":[36,73],"and":[37,70,80,114],"lower":[39],"memory":[40,83],"footprint.":[41],"The":[42],"applies":[45],"single-precision":[46],"arithmetic":[47],"computation":[50],"components":[51],"being":[52],"not":[53],"only":[54],"numerically":[55],"resilient":[56],"but":[57],"also":[58],"computationally":[59],"intensive.":[60],"Our":[61],"demonstrates":[64],"1.32,":[66],"1.15,":[67],"1.29,":[68],"1.09,":[69],"1.08\u00d7":[71],"improvements":[74],"using":[75],"24.95%,":[76],"24.74%,":[77],"24.89%,":[78],"24.48%,":[79],"24.20%":[81],"less":[82],"footprint":[84],"without":[85],"losing":[86],"any":[87],"compared":[90],"3-D":[96],"nonlinear":[97],"regression,":[98],"Lorenz":[100],"chaotic":[101,106],"series,":[103,108,113,120],"Mackey-Glass":[105],"sunspot":[110],"number":[111],"sea":[116],"surface":[117],"temperature":[118],"respectively.":[121]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2022,"cited_by_count":2}],"updated_date":"2026-07-20T07:56:41.581041","created_date":"2020-12-21T00:00:00"}
