{"id":"https://openalex.org/W7160240176","doi":"https://doi.org/10.48550/arxiv.2602.02056","title":"Ultrafast On-Chip Online Learning via Spline Locality in Kolmogorov-Arnold Networks","display_name":"Ultrafast On-Chip Online Learning via Spline Locality in Kolmogorov-Arnold Networks","publication_year":2026,"publication_date":"2026-02-02","ids":{"openalex":"https://openalex.org/W7160240176","doi":"https://doi.org/10.48550/arxiv.2602.02056"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2602.02056","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.02056","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2602.02056","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5135374976","display_name":"Duc Hoang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hoang, Duc","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124925570","display_name":"Aarush Gupta","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gupta, Aarush","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5135308736","display_name":"Philip Harris","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Harris, Philip","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12611","display_name":"Neural Networks and Reservoir Computing","score":0.40230000019073486,"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"}},"topics":[{"id":"https://openalex.org/T12611","display_name":"Neural Networks and Reservoir Computing","score":0.40230000019073486,"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/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.1542000025510788,"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":0.0835999995470047,"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/locality","display_name":"Locality","score":0.7106000185012817},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.5249000191688538},{"id":"https://openalex.org/keywords/perceptron","display_name":"Perceptron","score":0.4724999964237213},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.4440999925136566},{"id":"https://openalex.org/keywords/online-learning","display_name":"Online learning","score":0.41040000319480896},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.36550000309944153},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.35199999809265137},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.3416000008583069}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.722599983215332},{"id":"https://openalex.org/C2779808786","wikidata":"https://www.wikidata.org/wiki/Q6664603","display_name":"Locality","level":2,"score":0.7106000185012817},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.5249000191688538},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.4724999964237213},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.4440999925136566},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41110000014305115},{"id":"https://openalex.org/C2986087404","wikidata":"https://www.wikidata.org/wiki/Q15946010","display_name":"Online learning","level":2,"score":0.41040000319480896},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.36550000309944153},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3596999943256378},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3528999984264374},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.35199999809265137},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.3416000008583069},{"id":"https://openalex.org/C206345919","wikidata":"https://www.wikidata.org/wiki/Q20380951","display_name":"Resource (disambiguation)","level":2,"score":0.34130001068115234},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3095000088214874},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.2919999957084656},{"id":"https://openalex.org/C178596936","wikidata":"https://www.wikidata.org/wiki/Q844471","display_name":"Ultrashort pulse","level":3,"score":0.29030001163482666},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.27630001306533813},{"id":"https://openalex.org/C74270461","wikidata":"https://www.wikidata.org/wiki/Q1625299","display_name":"Locality-sensitive hashing","level":4,"score":0.27549999952316284},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.26460000872612},{"id":"https://openalex.org/C84114770","wikidata":"https://www.wikidata.org/wiki/Q46344","display_name":"Quantum","level":2,"score":0.2635999917984009},{"id":"https://openalex.org/C110875604","wikidata":"https://www.wikidata.org/wiki/Q75","display_name":"The Internet","level":2,"score":0.25369998812675476}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2602.02056","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.02056","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2602.02056","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.02056","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Ultrafast":[0],"online":[1,91,108,137],"learning":[2,138],"is":[3,131],"essential":[4],"for":[5,11,101],"high-frequency":[6],"systems,":[7],"such":[8],"as":[9],"controls":[10],"quantum":[12],"computing":[13],"and":[14,46,79,114,123],"nuclear":[15],"fusion,":[16],"where":[17],"adaptation":[18],"must":[19],"occur":[20],"on":[21,93],"sub-microsecond":[22,140],"timescales.":[23],"Meeting":[24],"these":[25,60],"requirements":[26],"demands":[27],"low-latency,":[28],"fixed-precision":[29],"computation":[30],"under":[31],"strict":[32],"memory":[33],"constraints,":[34],"a":[35,98,119],"regime":[36],"in":[37],"which":[38],"conventional":[39],"Multi-Layer":[40],"Perceptrons":[41],"(MLPs)":[42],"are":[43,72,82,110],"both":[44],"inefficient":[45],"numerically":[47],"unstable.":[48],"We":[49],"identify":[50],"key":[51],"properties":[52],"of":[53,121],"Kolmogorov-Arnold":[54],"Networks":[55],"(KANs)":[56],"that":[57,106],"align":[58],"with":[59],"constraints.":[61],"Specifically,":[62],"we":[63,104],"show":[64],"that:":[65],"(i)":[66],"KAN":[67],"updates":[68],"exploiting":[69],"B-spline":[70],"locality":[71],"sparse,":[73],"enabling":[74],"superior":[75],"on-chip":[76,102],"resource":[77],"scaling,":[78],"(ii)":[80],"KANs":[81],"inherently":[83],"robust":[84],"to":[85,134],"fixed-point":[86,90],"quantization.":[87],"By":[88],"implementing":[89],"training":[92],"Field-Programmable":[94],"Gate":[95],"Arrays":[96],"(FPGAs),":[97],"representative":[99],"platform":[100],"computation,":[103],"demonstrate":[105,135],"KAN-based":[107],"learners":[109],"significantly":[111],"more":[112],"efficient":[113],"expressive":[115],"than":[116],"MLPs":[117],"across":[118],"range":[120],"low-latency":[122],"resource-constrained":[124],"tasks.":[125],"To":[126],"our":[127],"knowledge,":[128],"this":[129],"work":[130],"the":[132],"first":[133],"model-free":[136],"at":[139],"latencies.":[141]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-05-06T00:00:00"}
