{"id":"https://openalex.org/W4210366739","doi":"https://doi.org/10.1109/tnnls.2022.3142726","title":"\u03f5-Approximation of Adaptive Leaning Rate Optimization Algorithms for Constrained Nonconvex Stochastic Optimization","display_name":"\u03f5-Approximation of Adaptive Leaning Rate Optimization Algorithms for Constrained Nonconvex Stochastic Optimization","publication_year":2022,"publication_date":"2022-01-29","ids":{"openalex":"https://openalex.org/W4210366739","doi":"https://doi.org/10.1109/tnnls.2022.3142726","pmid":"https://pubmed.ncbi.nlm.nih.gov/35089865"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2022.3142726","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2022.3142726","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5016609320","display_name":"Hideaki Iiduka","orcid":"https://orcid.org/0000-0001-9173-6723"},"institutions":[{"id":"https://openalex.org/I16656306","display_name":"Meiji University","ror":"https://ror.org/02rqvrp93","country_code":"JP","type":"education","lineage":["https://openalex.org/I16656306"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Hideaki Iiduka","raw_affiliation_strings":["Department of Computer Science, Meiji University, Kanagawa, Japan"],"raw_orcid":"https://orcid.org/0000-0001-9173-6723","affiliations":[{"raw_affiliation_string":"Department of Computer Science, Meiji University, Kanagawa, Japan","institution_ids":["https://openalex.org/I16656306"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5016609320"],"corresponding_institution_ids":["https://openalex.org/I16656306"],"apc_list":null,"apc_paid":null,"fwci":0.4645,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.6698791,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"34","issue":"10","first_page":"8108","last_page":"8115"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.9990000128746033,"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/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.9990000128746033,"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":0.994700014591217,"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/T10320","display_name":"Neural Networks and Applications","score":0.992900013923645,"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/stochastic-optimization","display_name":"Stochastic optimization","score":0.6261581182479858},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.5912508368492126},{"id":"https://openalex.org/keywords/stochastic-approximation","display_name":"Stochastic approximation","score":0.5683580040931702},{"id":"https://openalex.org/keywords/adaptive-optimization","display_name":"Adaptive optimization","score":0.5131540894508362},{"id":"https://openalex.org/keywords/optimization-algorithm","display_name":"Optimization algorithm","score":0.4868611693382263},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.47505924105644226},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.46681854128837585},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3707888126373291},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.04679664969444275}],"concepts":[{"id":"https://openalex.org/C194387892","wikidata":"https://www.wikidata.org/wiki/Q1747770","display_name":"Stochastic optimization","level":2,"score":0.6261581182479858},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.5912508368492126},{"id":"https://openalex.org/C55479107","wikidata":"https://www.wikidata.org/wiki/Q97663916","display_name":"Stochastic approximation","level":3,"score":0.5683580040931702},{"id":"https://openalex.org/C149672232","wikidata":"https://www.wikidata.org/wiki/Q337048","display_name":"Adaptive optimization","level":2,"score":0.5131540894508362},{"id":"https://openalex.org/C2987595161","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Optimization algorithm","level":2,"score":0.4868611693382263},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.47505924105644226},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.46681854128837585},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3707888126373291},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.04679664969444275},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2022.3142726","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2022.3142726","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:35089865","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/35089865","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on neural networks and learning systems","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5366413431","display_name":"Riemannian Fixed Point Optimization Algorithm and Its Application to Machine Learning","funder_award_id":"21K11773","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"}],"funders":[{"id":"https://openalex.org/F4320334764","display_name":"Japan Society for the Promotion of Science","ror":"https://ror.org/00hhkn466"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":46,"referenced_works":["https://openalex.org/W104184427","https://openalex.org/W1498436455","https://openalex.org/W1514535095","https://openalex.org/W1516681311","https://openalex.org/W1522301498","https://openalex.org/W1988720110","https://openalex.org/W1992208280","https://openalex.org/W1994616650","https://openalex.org/W2146502635","https://openalex.org/W2155894447","https://openalex.org/W2785523195","https://openalex.org/W2810882972","https://openalex.org/W2936995161","https://openalex.org/W2963563140","https://openalex.org/W3034547948","https://openalex.org/W3040617750","https://openalex.org/W3099368215","https://openalex.org/W3100197791","https://openalex.org/W3103900341","https://openalex.org/W3127131334","https://openalex.org/W3130950075","https://openalex.org/W3197228570","https://openalex.org/W4229650096","https://openalex.org/W4288284572","https://openalex.org/W4289300273","https://openalex.org/W4301791716","https://openalex.org/W4385245566","https://openalex.org/W6604254268","https://openalex.org/W6630875275","https://openalex.org/W6631190155","https://openalex.org/W6681435938","https://openalex.org/W6683107984","https://openalex.org/W6739901393","https://openalex.org/W6747620207","https://openalex.org/W6753122105","https://openalex.org/W6753892653","https://openalex.org/W6756592394","https://openalex.org/W6761030284","https://openalex.org/W6765175657","https://openalex.org/W6773730267","https://openalex.org/W6774531910","https://openalex.org/W6779669310","https://openalex.org/W6784591795","https://openalex.org/W6785596849","https://openalex.org/W6786291537","https://openalex.org/W6790165035"],"related_works":["https://openalex.org/W2124181538","https://openalex.org/W3207830353","https://openalex.org/W4286899070","https://openalex.org/W4323366756","https://openalex.org/W2734989445","https://openalex.org/W2403770454","https://openalex.org/W4285259204","https://openalex.org/W4388209346","https://openalex.org/W3012647659","https://openalex.org/W4210366739"],"abstract_inverted_index":{"This":[0],"brief":[1],"considers":[2],"constrained":[3],"nonconvex":[4],"stochastic":[5,66],"finite-sum":[6],"and":[7,22,36,40,65],"online":[8],"optimization":[9,15],"in":[10,38],"deep":[11],"neural":[12],"networks.":[13],"Adaptive-learning-rate":[14],"algorithms":[16],"(ALROAs),":[17],"such":[18],"as":[19],"Adam,":[20],"AMSGrad,":[21],"their":[23],"variants,":[24],"have":[25],"widely":[26],"been":[27],"used":[28],"for":[29,52],"these":[30,53],"optimizations":[31],"because":[32],"they":[33],"are":[34,49],"powerful":[35],"useful":[37],"theory":[39],"practice.":[41],"Here,":[42],"it":[43],"is":[44],"shown":[45],"that":[46],"the":[47,57,76],"ALROAs":[48],"\u03f5":[50,73],"-approximations":[51,74],"optimizations.":[54],"We":[55],"provide":[56],"learning":[58],"rates,":[59],"mini-batch":[60],"sizes,":[61],"number":[62],"of":[63,75],"iterations,":[64],"gradient":[67],"complexity":[68],"with":[69],"which":[70],"to":[71],"achieve":[72],"algorithms.":[77]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":1}],"updated_date":"2026-07-29T09:40:50.615796","created_date":"2025-10-10T00:00:00"}
