{"id":"https://openalex.org/W4407729147","doi":"https://doi.org/10.1093/comjnl/bxaf012","title":"Learning to optimize based on rate decay","display_name":"Learning to optimize based on rate decay","publication_year":2025,"publication_date":"2025-02-17","ids":{"openalex":"https://openalex.org/W4407729147","doi":"https://doi.org/10.1093/comjnl/bxaf012"},"language":"en","primary_location":{"id":"doi:10.1093/comjnl/bxaf012","is_oa":false,"landing_page_url":"https://doi.org/10.1093/comjnl/bxaf012","pdf_url":null,"source":{"id":"https://openalex.org/S44643521","display_name":"The Computer Journal","issn_l":"0010-4620","issn":["0010-4620","1460-2067"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310311648","host_organization_name":"Oxford University Press","host_organization_lineage":["https://openalex.org/P4310311648","https://openalex.org/P4310311647"],"host_organization_lineage_names":["Oxford University Press","University of Oxford"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The Computer Journal","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5107954697","display_name":"W.G. Ma","orcid":null},"institutions":[{"id":"https://openalex.org/I111753288","display_name":"Fujian Normal University","ror":"https://ror.org/020azk594","country_code":"CN","type":"education","lineage":["https://openalex.org/I111753288"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Wenmin Ma","raw_affiliation_strings":["School of Mathematics and Statistics , Fujian Normal University, Fuzhou 350117, Fujian,","School of Mathematics and Statistics, Fujian Normal University, Fuzhou 350117, Fujian, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mathematics and Statistics , Fujian Normal University, Fuzhou 350117, Fujian,","institution_ids":["https://openalex.org/I111753288"]},{"raw_affiliation_string":"School of Mathematics and Statistics, Fujian Normal University, Fuzhou 350117, Fujian, China","institution_ids":["https://openalex.org/I111753288"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5107954697"],"corresponding_institution_ids":["https://openalex.org/I111753288"],"apc_list":{"value":2635,"currency":"GBP","value_usd":3232},"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.01089774,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"68","issue":"8","first_page":"908","last_page":"925"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12072","display_name":"Machine Learning and Algorithms","score":0.9997000098228455,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.9997000098228455,"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9986000061035156,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9986000061035156,"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/computer-science","display_name":"Computer science","score":0.5585595369338989}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5585595369338989}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1093/comjnl/bxaf012","is_oa":false,"landing_page_url":"https://doi.org/10.1093/comjnl/bxaf012","pdf_url":null,"source":{"id":"https://openalex.org/S44643521","display_name":"The Computer Journal","issn_l":"0010-4620","issn":["0010-4620","1460-2067"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310311648","host_organization_name":"Oxford University Press","host_organization_lineage":["https://openalex.org/P4310311648","https://openalex.org/P4310311647"],"host_organization_lineage_names":["Oxford University Press","University of Oxford"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The Computer Journal","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W1806891645","https://openalex.org/W1892182570","https://openalex.org/W1994616650","https://openalex.org/W2026258334","https://openalex.org/W2029469881","https://openalex.org/W2038497950","https://openalex.org/W2064675550","https://openalex.org/W2107878631","https://openalex.org/W2110485445","https://openalex.org/W2146502635","https://openalex.org/W2157331557","https://openalex.org/W2560674852","https://openalex.org/W2963775850","https://openalex.org/W2990346675","https://openalex.org/W3103370507","https://openalex.org/W3129850285","https://openalex.org/W3137965023","https://openalex.org/W4211092921","https://openalex.org/W4292779060","https://openalex.org/W4311114086","https://openalex.org/W6631190155","https://openalex.org/W6681435938","https://openalex.org/W6717367658","https://openalex.org/W6729210268","https://openalex.org/W6735618850","https://openalex.org/W6735961515","https://openalex.org/W6759546789","https://openalex.org/W6771626834","https://openalex.org/W6778881932","https://openalex.org/W6778883912","https://openalex.org/W6792219651","https://openalex.org/W6850115296","https://openalex.org/W6853137691"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"Abstract":[0],"Learning":[1],"to":[2,12,48,94,117,119,140],"optimize":[3],"(L2O)":[4],"is":[5],"a":[6,30,35,85],"technique":[7],"that":[8,156],"uses":[9],"neural":[10],"networks":[11],"learn":[13],"optimization":[14,23,37,80,115,121,143,165],"algorithms":[15],"automatically.":[16],"While":[17],"it":[18],"holds":[19],"promise":[20],"for":[21,113],"diverse":[22],"problems,":[24],"achieving":[25],"consistently":[26],"ideal":[27],"results":[28],"remains":[29],"challenge.":[31],"Typically,":[32],"L2O":[33,74,93,107],"through":[34],"parameterized":[36],"method":[38],"(i.e.":[39],"\u201c":[40],"optimizer\u201d)":[41],"learns":[42],"from":[43,64,149],"training":[44,66],"samples":[45],"and":[46,108,152],"generalizes":[47],"test":[49,58],"tasks":[50,59],"with":[51],"the":[52,56,65,72,91,96,103,128,134,138,146],"same":[53],"distribution.":[54,68],"However,":[55],"new":[57],"usually":[60],"have":[61],"some":[62],"deviation":[63],"set":[67],"In":[69],"this":[70],"case,":[71],"generic":[73,92],"methods":[75,159],"may":[76],"not":[77],"produce":[78],"good":[79],"results.":[81,144],"Thus,":[82],"we":[83,124],"introduce":[84],"step-size":[86],"control":[87,101],"mechanism":[88],"based":[89],"on":[90],"solve":[95],"common":[97],"problem":[98],"of":[99,102,137],"insufficient":[100],"iteration":[104],"amplitude":[105],"in":[106],"adopt":[109],"different":[110],"update":[111],"strategies":[112],"various":[114],"problems":[116],"adapt":[118],"complex":[120],"scenarios.":[122],"Additionally,":[123],"also":[125],"innovatively":[126],"use":[127],"gated":[129],"recurrent":[130],"unit":[131],"network":[132],"as":[133],"core":[135],"model":[136],"optimizer":[139],"achieve":[141],"better":[142,162],"Finally,":[145],"experimental":[147],"outcomes":[148],"numerical":[150],"simulations":[151],"real-world":[153],"datasets":[154],"show":[155],"our":[157],"proposed":[158],"are":[160],"significantly":[161],"than":[163],"other":[164],"algorithms.":[166]},"counts_by_year":[],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}