{"id":"https://openalex.org/W7127649834","doi":"https://doi.org/10.48550/arxiv.2602.02767","title":"Provable Effects of Data Replay in Continual Learning: A Feature Learning Perspective","display_name":"Provable Effects of Data Replay in Continual Learning: A Feature Learning Perspective","publication_year":2026,"publication_date":"2026-02-02","ids":{"openalex":"https://openalex.org/W7127649834","doi":"https://doi.org/10.48550/arxiv.2602.02767"},"language":null,"primary_location":{"id":"pmh:doi:10.48550/arxiv.2602.02767","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"type":"article","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/A5125030131","display_name":"Meng Ding","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ding, Meng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125040040","display_name":"Jinhui Xu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xu, Jinhui","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5071973105","display_name":"Kaiyi Ji","orcid":"https://orcid.org/0000-0002-9533-0058"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ji, Kaiyi","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":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.14455153,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"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":0.9833999872207642,"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":0.9833999872207642,"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/T11448","display_name":"Face recognition and analysis","score":0.0024999999441206455,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.000699999975040555,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/task","display_name":"Task (project management)","score":0.6190999746322632},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5871000289916992},{"id":"https://openalex.org/keywords/perspective","display_name":"Perspective (graphical)","score":0.5717999935150146},{"id":"https://openalex.org/keywords/forgetting","display_name":"Forgetting","score":0.5687999725341797},{"id":"https://openalex.org/keywords/memorization","display_name":"Memorization","score":0.48019999265670776},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.4724000096321106},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4657999873161316},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.42100000381469727},{"id":"https://openalex.org/keywords/sequence-learning","display_name":"Sequence learning","score":0.4133000075817108},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.40630000829696655}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7943000197410583},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6708999872207642},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.663100004196167},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6190999746322632},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5871000289916992},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.5717999935150146},{"id":"https://openalex.org/C7149132","wikidata":"https://www.wikidata.org/wiki/Q1377840","display_name":"Forgetting","level":2,"score":0.5687999725341797},{"id":"https://openalex.org/C30038468","wikidata":"https://www.wikidata.org/wiki/Q4354775","display_name":"Memorization","level":2,"score":0.48019999265670776},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4724000096321106},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4657999873161316},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.42100000381469727},{"id":"https://openalex.org/C40506919","wikidata":"https://www.wikidata.org/wiki/Q7452469","display_name":"Sequence learning","level":2,"score":0.4133000075817108},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.40630000829696655},{"id":"https://openalex.org/C28006648","wikidata":"https://www.wikidata.org/wiki/Q6934509","display_name":"Multi-task learning","level":3,"score":0.39800000190734863},{"id":"https://openalex.org/C24138899","wikidata":"https://www.wikidata.org/wiki/Q17141258","display_name":"Instance-based learning","level":3,"score":0.38499999046325684},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.37880000472068787},{"id":"https://openalex.org/C2780735816","wikidata":"https://www.wikidata.org/wiki/Q28324931","display_name":"Incremental learning","level":2,"score":0.3441999852657318},{"id":"https://openalex.org/C77967617","wikidata":"https://www.wikidata.org/wiki/Q4677561","display_name":"Active learning (machine learning)","level":2,"score":0.33739998936653137},{"id":"https://openalex.org/C66905080","wikidata":"https://www.wikidata.org/wiki/Q17005494","display_name":"Binary classification","level":3,"score":0.33230000734329224},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.3163999915122986},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.31520000100135803},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.30880001187324524},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.3077999949455261},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.3075999915599823},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.30230000615119934},{"id":"https://openalex.org/C2781039887","wikidata":"https://www.wikidata.org/wiki/Q1391724","display_name":"Factor (programming language)","level":2,"score":0.29280000925064087},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.2799000144004822},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.2784999907016754},{"id":"https://openalex.org/C199190896","wikidata":"https://www.wikidata.org/wiki/Q3509276","display_name":"Learning classifier system","level":3,"score":0.27410000562667847},{"id":"https://openalex.org/C176248197","wikidata":"https://www.wikidata.org/wiki/Q458526","display_name":"Probably approximately correct learning","level":4,"score":0.2628999948501587}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:doi:10.48550/arxiv.2602.02767","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},{"id":"doi:10.48550/arxiv.2602.02767","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.02767","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":"pmh:doi:10.48550/arxiv.2602.02767","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"sustainable_development_goals":[{"display_name":"No poverty","id":"https://metadata.un.org/sdg/1","score":0.47609591484069824}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Continual":[0],"learning":[1,30,93,97,166,184,210],"(CL)":[2],"aims":[3],"to":[4],"train":[5],"models":[6],"on":[7,15,117],"a":[8,82,95,100,111,172],"sequence":[9],"of":[10,62,185],"tasks":[11,144,180,187],"while":[12],"retaining":[13],"performance":[14],"previously":[16],"learned":[17],"ones.":[18],"A":[19],"core":[20],"challenge":[21],"in":[22,91],"this":[23,78],"setting":[24],"is":[25,70],"catastrophic":[26,192],"forgetting,":[27],"where":[28,41,66],"new":[29],"interferes":[31],"with":[32,153],"past":[33,42,68],"knowledge.":[34],"Among":[35],"various":[36],"mitigation":[37],"strategies,":[38],"data-replay":[39,89],"methods,":[40],"samples":[43],"are":[44,47,56],"periodically":[45],"revisited,":[46],"considered":[48],"simple":[49],"yet":[50],"effective,":[51],"especially":[52],"when":[53,138],"memory":[54],"constraints":[55],"relaxed.":[57],"However,":[58],"the":[59,106,139,146,206],"theoretical":[60,84,197],"effectiveness":[61],"full":[63,88,136],"data":[64,69,102,157],"replay,":[65],"all":[67],"accessible":[71],"during":[72],"training,":[73],"remains":[74],"largely":[75],"unexplored.":[76],"In":[77],"paper,":[79],"we":[80,104,170],"present":[81],"comprehensive":[83],"framework":[85],"for":[86],"analyzing":[87],"training":[90],"continual":[92],"from":[94,142,148],"feature":[96],"perspective.":[98],"Adopting":[99],"multi-view":[101],"model,":[103],"identify":[105],"signal-to-noise":[107],"ratio":[108],"(SNR)":[109],"as":[110],"critical":[112],"factor":[113],"affecting":[114],"forgetting.":[115,193],"Focusing":[116],"task-incremental":[118],"binary":[119],"classification":[120],"across":[121,214],"$M$":[122],"tasks,":[123],"our":[124,196],"analysis":[125],"verifies":[126],"two":[127],"key":[128],"conclusions:":[129],"(1)":[130],"forgetting":[131],"can":[132,159],"still":[133],"occur":[134],"under":[135],"replay":[137,158],"cumulative":[140],"noise":[141,212],"later":[143],"dominates":[145],"signal":[147,155,209],"earlier":[149,161],"ones;":[150],"and":[151,201,211,217],"(2)":[152],"sufficient":[154],"accumulation,":[156],"recover":[160],"tasks-even":[162],"if":[163],"their":[164],"initial":[165],"was":[167],"poor.":[168],"Notably,":[169],"uncover":[171],"novel":[173],"insight":[174],"into":[175],"task":[176,218],"ordering:":[177],"prioritizing":[178],"higher-signal":[179],"not":[181],"only":[182],"facilitates":[183],"lower-signal":[186],"but":[188],"also":[189],"helps":[190],"prevent":[191],"We":[194],"validate":[195],"findings":[198],"through":[199],"synthetic":[200],"real-world":[202],"experiments":[203],"that":[204],"visualize":[205],"interplay":[207],"between":[208],"memorization":[213],"varying":[215],"SNRs":[216],"correlation":[219],"regimes.":[220]},"counts_by_year":[],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2026-02-06T00:00:00"}