{"id":"https://openalex.org/W7135100600","doi":"https://doi.org/10.48550/arxiv.2603.10095","title":"Rethinking Adam for Time Series Forecasting: A Simple Heuristic to Improve Optimization under Distribution Shifts","display_name":"Rethinking Adam for Time Series Forecasting: A Simple Heuristic to Improve Optimization under Distribution Shifts","publication_year":2026,"publication_date":"2026-03-10","ids":{"openalex":"https://openalex.org/W7135100600","doi":"https://doi.org/10.48550/arxiv.2603.10095"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.10095","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.10095","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":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.2603.10095","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5128836452","display_name":"Yuze Dong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dong, Yuze","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5128833275","display_name":"Jinsong Wu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wu, Jinsong","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/T12761","display_name":"Data Stream Mining Techniques","score":0.5720000267028809,"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/T12761","display_name":"Data Stream Mining Techniques","score":0.5720000267028809,"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/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.10639999806880951,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11918","display_name":"Forecasting Techniques and Applications","score":0.09730000048875809,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/adaptability","display_name":"Adaptability","score":0.6424000263214111},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5902000069618225},{"id":"https://openalex.org/keywords/simple","display_name":"Simple (philosophy)","score":0.5619000196456909},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.545199990272522},{"id":"https://openalex.org/keywords/heuristic","display_name":"Heuristic","score":0.5234000086784363},{"id":"https://openalex.org/keywords/core","display_name":"Core (optical fiber)","score":0.43779999017715454},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.41179999709129333}],"concepts":[{"id":"https://openalex.org/C177606310","wikidata":"https://www.wikidata.org/wiki/Q5674297","display_name":"Adaptability","level":2,"score":0.6424000263214111},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6215999722480774},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5902000069618225},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.5619000196456909},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.5595999956130981},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.545199990272522},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.5234000086784363},{"id":"https://openalex.org/C2164484","wikidata":"https://www.wikidata.org/wiki/Q5170150","display_name":"Core (optical fiber)","level":2,"score":0.43779999017715454},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.41179999709129333},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.4068000018596649},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.39329999685287476},{"id":"https://openalex.org/C110121322","wikidata":"https://www.wikidata.org/wiki/Q865811","display_name":"Distribution (mathematics)","level":2,"score":0.3824000060558319},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3294999897480011},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3163999915122986},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.2768000066280365},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.27079999446868896},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.2678000032901764},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.2671999931335449},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.26109999418258667},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.258899986743927}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.10095","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.10095","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":"doi:10.48550/arxiv.2603.10095","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.10095","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":false,"raw_source_name":null,"raw_type":"Preprint"},"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":{"Time-series":[0],"forecasting":[1,48,114,156],"often":[2],"faces":[3],"challenges":[4],"from":[5,76],"non-stationarity,":[6],"particularly":[7],"distributional":[8,87],"drift,":[9],"where":[10],"the":[11,22,44,73,77,91,117,121,143],"data":[12],"distribution":[13],"evolves":[14],"over":[15],"time.":[16],"This":[17,81],"dynamic":[18],"behavior":[19],"can":[20],"undermine":[21],"effectiveness":[23],"of":[24,46,129,147],"adaptive":[25],"optimizers,":[26],"such":[27],"as":[28,149],"Adam,":[29],"which":[30],"are":[31],"typically":[32],"designed":[33],"for":[34,154],"stationary":[35],"objectives.":[36],"In":[37],"this":[38],"paper,":[39],"we":[40,65],"revisit":[41],"Adam":[42],"in":[43,131,135],"context":[45],"non-stationary":[47,159],"and":[49,95,106,112,133,145],"identify":[50],"that":[51,71],"its":[52],"second-order":[53,74],"bias":[54],"correction":[55,75],"limits":[56],"responsiveness":[57],"to":[58,86,138],"shifting":[59],"loss":[60],"landscapes.":[61],"To":[62],"address":[63],"this,":[64],"propose":[66],"TS_Adam,":[67],"a":[68],"lightweight":[69],"variant":[70],"removes":[72],"learning":[78],"rate":[79],"computation.":[80],"simple":[82],"modification":[83],"improves":[84,108],"adaptability":[85],"drift":[88],"while":[89],"preserving":[90],"optimizer":[92],"core":[93],"structure":[94],"requiring":[96],"no":[97],"additional":[98],"hyperparameters.":[99],"TS_Adam":[100,148],"integrates":[101],"easily":[102],"into":[103],"existing":[104],"models":[105],"consistently":[107],"performance":[109],"across":[110],"long-":[111],"short-term":[113],"tasks.":[115],"On":[116],"ETT":[118],"datasets":[119],"with":[120],"MICN":[122],"model,":[123],"it":[124],"achieves":[125],"an":[126,150],"average":[127],"reduction":[128],"12.8%":[130],"MSE":[132],"5.7%":[134],"MAE":[136],"compared":[137],"Adam.":[139],"These":[140],"results":[141],"underscore":[142],"practicality":[144],"versatility":[146],"effective":[151],"optimization":[152],"strategy":[153],"real-world":[155],"scenarios":[157],"involving":[158],"data.":[160],"Code":[161],"is":[162],"available":[163],"at:":[164],"https://github.com/DD-459-1/TS_Adam.":[165]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-03-13T00:00:00"}
