{"id":"https://openalex.org/W7127083337","doi":"https://doi.org/10.48550/arxiv.2601.22200","title":"Adaptive Benign Overfitting (ABO): Overparameterized RLS for Online Learning in Non-stationary Time-series","display_name":"Adaptive Benign Overfitting (ABO): Overparameterized RLS for Online Learning in Non-stationary Time-series","publication_year":2026,"publication_date":"2026-01-29","ids":{"openalex":"https://openalex.org/W7127083337","doi":"https://doi.org/10.48550/arxiv.2601.22200"},"language":null,"primary_location":{"id":"pmh:doi:10.48550/arxiv.2601.22200","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":null,"any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5120305626","display_name":"Luis Ontaneda Mijares","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mijares, Luis Ontaneda","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5051759229","display_name":"Nick Firoozye","orcid":"https://orcid.org/0000-0002-6460-0406"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Firoozye, Nick","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/T11326","display_name":"Stock Market Forecasting Methods","score":0.28760001063346863,"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":0.28760001063346863,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.09969999641180038,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T12761","display_name":"Data Stream Mining Techniques","score":0.06930000334978104,"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/overfitting","display_name":"Overfitting","score":0.8780999779701233},{"id":"https://openalex.org/keywords/bounded-function","display_name":"Bounded function","score":0.43700000643730164},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.4359000027179718},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.430400013923645},{"id":"https://openalex.org/keywords/divergence","display_name":"Divergence (linguistics)","score":0.41119998693466187},{"id":"https://openalex.org/keywords/adaptability","display_name":"Adaptability","score":0.40119999647140503},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4011000096797943},{"id":"https://openalex.org/keywords/interpolation","display_name":"Interpolation (computer graphics)","score":0.39640000462532043}],"concepts":[{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.8780999779701233},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5371999740600586},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4805000126361847},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.460999995470047},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.45329999923706055},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4465999901294708},{"id":"https://openalex.org/C34388435","wikidata":"https://www.wikidata.org/wiki/Q2267362","display_name":"Bounded function","level":2,"score":0.43700000643730164},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.4359000027179718},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.430400013923645},{"id":"https://openalex.org/C207390915","wikidata":"https://www.wikidata.org/wiki/Q1230525","display_name":"Divergence (linguistics)","level":2,"score":0.41119998693466187},{"id":"https://openalex.org/C177606310","wikidata":"https://www.wikidata.org/wiki/Q5674297","display_name":"Adaptability","level":2,"score":0.40119999647140503},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4011000096797943},{"id":"https://openalex.org/C137800194","wikidata":"https://www.wikidata.org/wiki/Q11713455","display_name":"Interpolation (computer graphics)","level":3,"score":0.39640000462532043},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3650999963283539},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.3617999851703644},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.35920000076293945},{"id":"https://openalex.org/C2776879701","wikidata":"https://www.wikidata.org/wiki/Q25048660","display_name":"Multiple kernel learning","level":4,"score":0.3589000105857849},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.29809999465942383},{"id":"https://openalex.org/C2986087404","wikidata":"https://www.wikidata.org/wiki/Q15946010","display_name":"Online learning","level":2,"score":0.2867000102996826},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2825999855995178},{"id":"https://openalex.org/C125014702","wikidata":"https://www.wikidata.org/wiki/Q4680749","display_name":"Adaptive learning","level":2,"score":0.27959999442100525},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.27639999985694885}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:doi:10.48550/arxiv.2601.22200","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},{"id":"doi:10.48550/arxiv.2601.22200","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2601.22200","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:doi:10.48550/arxiv.2601.22200","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Overparameterized":[0],"models":[1],"have":[2],"recently":[3],"challenged":[4],"conventional":[5],"learning":[6,163],"theory":[7],"by":[8],"exhibiting":[9],"improved":[10],"generalization":[11],"beyond":[12],"the":[13,30,75,97,109],"interpolation":[14],"limit,":[15],"a":[16,39,148,160],"phenomenon":[17],"known":[18],"as":[19],"benign":[20,157],"overfitting.":[21],"This":[22],"work":[23],"introduces":[24],"Adaptive":[25],"Benign":[26],"Overfitting":[27],"(ABO),":[28],"extending":[29],"recursive":[31],"least-squares":[32],"(RLS)":[33],"framework":[34],"to":[35,64,85,117,131],"this":[36],"regime":[37],"through":[38],"numerically":[40],"stable":[41,104,161],"formulation":[42],"based":[43],"on":[44,90],"orthogonal-triangular":[45],"updates.":[46],"A":[47],"QR-based":[48],"exponentially":[49],"weighted":[50],"RLS":[51,81],"(QR-EWRLS)":[52],"algorithm":[53],"is":[54,127],"introduced,":[55],"combining":[56],"random":[57],"Fourier":[58],"feature":[59],"mappings":[60],"with":[61,79],"forgetting-factor":[62],"regularization":[63],"enable":[65],"online":[66,162],"adaptation":[67],"under":[68],"non-stationary":[69],"conditions.":[70],"The":[71,145],"orthogonal":[72],"decomposition":[73],"prevents":[74],"numerical":[76],"divergence":[77],"associated":[78],"covariance-form":[80],"while":[82,107,135],"retaining":[83],"adaptability":[84],"evolving":[86],"data":[87],"distributions.":[88],"Experiments":[89],"nonlinear":[91],"synthetic":[92],"time":[93],"series":[94],"confirm":[95],"that":[96,125],"proposed":[98],"approach":[99],"maintains":[100],"bounded":[101],"residuals":[102],"and":[103,121,142,156],"condition":[105],"numbers":[106],"reproducing":[108],"double-descent":[110],"behavior":[111],"characteristic":[112],"of":[113,139],"overparameterized":[114],"models.":[115],"Applications":[116],"forecasting":[118],"foreign":[119],"exchange":[120],"electricity":[122],"demand":[123],"show":[124],"ABO":[126],"highly":[128],"accurate":[129],"(comparable":[130],"baseline":[132],"kernel":[133,154],"methods)":[134],"achieving":[136],"speed":[137],"improvements":[138],"between":[140],"20":[141],"40":[143],"percent.":[144],"results":[146],"provide":[147],"unified":[149],"view":[150],"linking":[151],"adaptive":[152],"filtering,":[153],"approximation,":[155],"overfitting":[158],"within":[159],"framework.":[164]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-02-03T00:00:00"}