{"id":"https://openalex.org/W7138927025","doi":"https://doi.org/10.48550/arxiv.2603.17548","title":"CLeAN: Continual Learning Adaptive Normalization in Dynamic Environments","display_name":"CLeAN: Continual Learning Adaptive Normalization in Dynamic Environments","publication_year":2026,"publication_date":"2026-03-18","ids":{"openalex":"https://openalex.org/W7138927025","doi":"https://doi.org/10.48550/arxiv.2603.17548"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.17548","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.17548","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":"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.2603.17548","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5130097366","display_name":"Isabella Marasco","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Marasco, Isabella","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130018498","display_name":"Davide Evangelista","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Evangelista, Davide","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125441465","display_name":"Elena Loli Piccolomini","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Piccolomini, Elena Loli","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5073709427","display_name":"Michele Colajanni","orcid":"https://orcid.org/0000-0002-9499-1559"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Colajanni, Michele","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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.7318999767303467,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.7318999767303467,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.04430000111460686,"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/T12761","display_name":"Data Stream Mining Techniques","score":0.029999999329447746,"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/normalization","display_name":"Normalization (sociology)","score":0.8866999745368958},{"id":"https://openalex.org/keywords/adaptive-learning","display_name":"Adaptive learning","score":0.4350000023841858},{"id":"https://openalex.org/keywords/incremental-learning","display_name":"Incremental learning","score":0.41780000925064087},{"id":"https://openalex.org/keywords/database-normalization","display_name":"Database normalization","score":0.40689998865127563},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.37130001187324524},{"id":"https://openalex.org/keywords/perspective","display_name":"Perspective (graphical)","score":0.3003999888896942}],"concepts":[{"id":"https://openalex.org/C136886441","wikidata":"https://www.wikidata.org/wiki/Q926129","display_name":"Normalization (sociology)","level":2,"score":0.8866999745368958},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7243000268936157},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6888999938964844},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6157000064849854},{"id":"https://openalex.org/C125014702","wikidata":"https://www.wikidata.org/wiki/Q4680749","display_name":"Adaptive learning","level":2,"score":0.4350000023841858},{"id":"https://openalex.org/C2780735816","wikidata":"https://www.wikidata.org/wiki/Q28324931","display_name":"Incremental learning","level":2,"score":0.41780000925064087},{"id":"https://openalex.org/C162984825","wikidata":"https://www.wikidata.org/wiki/Q339072","display_name":"Database normalization","level":3,"score":0.40689998865127563},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.37130001187324524},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.3003999888896942},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2896000146865845},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.28619998693466187},{"id":"https://openalex.org/C52970973","wikidata":"https://www.wikidata.org/wiki/Q2497134","display_name":"Adaptive system","level":2,"score":0.28600001335144043},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.2696000039577484},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.26669999957084656},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.26489999890327454},{"id":"https://openalex.org/C207685749","wikidata":"https://www.wikidata.org/wiki/Q2088941","display_name":"Domain knowledge","level":2,"score":0.25220000743865967}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.17548","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.17548","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":"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.2603.17548","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.17548","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":"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":[{"display_name":"Industry, innovation and infrastructure","score":0.4673054814338684,"id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Artificial":[0],"intelligence":[1],"systems":[2],"predominantly":[3],"rely":[4],"on":[5,135,159,188],"static":[6],"data":[7,24,40,55,130,161],"distributions,":[8],"making":[9],"them":[10],"ineffective":[11],"in":[12,51,99,175,196],"dynamic":[13,197],"real-world":[14],"environments,":[15],"such":[16,60],"as":[17,61],"cybersecurity,":[18],"autonomous":[19],"transportation,":[20],"or":[21],"finance,":[22],"where":[23],"shifts":[25],"frequently.":[26],"Continual":[27,85],"learning":[28,98,141,198],"offers":[29],"a":[30,46,90,185],"potential":[31],"solution":[32],"by":[33],"enabling":[34,123],"models":[35],"to":[36,66,126,128,193],"learn":[37],"from":[38],"sequential":[39,75],"while":[41],"retaining":[42],"prior":[43],"knowledge.":[44],"However,":[45],"critical":[47],"and":[48,138,148,179],"underexplored":[49],"issue":[50],"this":[52,81],"domain":[53],"is":[54,71],"normalization.":[56],"Conventional":[57],"normalization":[58,93,174,192],"methods,":[59],"min-max":[62],"scaling,":[63],"presuppose":[64],"access":[65],"the":[67,74,104,124,170,177,189],"entire":[68],"dataset,":[69],"which":[70],"incongruent":[72],"with":[73],"nature":[76],"of":[77,106,172,181,191],"continual":[78,97,140],"learning.":[79],"In":[80],"paper":[82],"we":[83,150],"introduce":[84],"Learning":[86],"Adaptive":[87],"Normalization":[88],"(CLeAN),":[89],"novel":[91,186],"adaptive":[92,173],"technique":[94],"designed":[95],"for":[96],"tabular":[100,182],"data.":[101],"CLeAN":[102,153],"involves":[103],"estimation":[105],"global":[107],"feature":[108],"scales":[109],"using":[110],"learnable":[111],"parameters":[112],"that":[113,152],"are":[114],"updated":[115],"via":[116],"an":[117],"Exponential":[118],"Moving":[119],"Average":[120],"(EMA)":[121],"module,":[122],"model":[125,157],"adapt":[127],"evolving":[129],"distributions.":[131],"Through":[132],"comprehensive":[133],"evaluations":[134],"two":[136],"datasets":[137],"various":[139],"strategies,":[142],"including":[143],"Resevoir":[144],"Experience":[145],"Replay,":[146],"A-GEM,":[147],"EwC":[149],"demonstrate":[151],"not":[154],"only":[155],"improves":[156],"performance":[158],"new":[160],"but":[162],"also":[163],"mitigates":[164],"catastrophic":[165],"forgetting.":[166],"The":[167],"findings":[168],"underscore":[169],"importance":[171],"enhancing":[176],"stability":[178],"effectiveness":[180],"data,":[183],"offering":[184],"perspective":[187],"use":[190],"preserve":[194],"knowledge":[195],"environments.":[199]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-03-20T00:00:00"}