{"id":"https://openalex.org/W4404787468","doi":"https://doi.org/10.1109/tsp.2024.3505266","title":"Nonparametric Bellman Mappings for Reinforcement Learning: Application to Robust Adaptive Filtering","display_name":"Nonparametric Bellman Mappings for Reinforcement Learning: Application to Robust Adaptive Filtering","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4404787468","doi":"https://doi.org/10.1109/tsp.2024.3505266"},"language":"en","primary_location":{"id":"doi:10.1109/tsp.2024.3505266","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2024.3505266","pdf_url":null,"source":{"id":"https://openalex.org/S168680287","display_name":"IEEE Transactions on Signal Processing","issn_l":"1053-587X","issn":["1053-587X","1941-0476"],"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 Signal Processing","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/A5115444776","display_name":"Yuki AKIYAMA","orcid":"https://orcid.org/0009-0008-7001-1035"},"institutions":[{"id":"https://openalex.org/I90023481","display_name":"National Institute of Information and Communications Technology","ror":"https://ror.org/016bgq349","country_code":"JP","type":"facility","lineage":["https://openalex.org/I90023481"]},{"id":"https://openalex.org/I4400009020","display_name":"Institute of Science Tokyo","ror":"https://ror.org/05dqf9946","country_code":null,"type":"education","lineage":["https://openalex.org/I4400009020"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Yuki Akiyama","raw_affiliation_strings":["Department of Information and Communications Engineering, Institute of Science Tokyo, Yokohama, Japan"],"affiliations":[{"raw_affiliation_string":"Department of Information and Communications Engineering, Institute of Science Tokyo, Yokohama, Japan","institution_ids":["https://openalex.org/I90023481","https://openalex.org/I4400009020"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052911807","display_name":"Minh Vu","orcid":"https://orcid.org/0009-0009-1441-8276"},"institutions":[{"id":"https://openalex.org/I4400009020","display_name":"Institute of Science Tokyo","ror":"https://ror.org/05dqf9946","country_code":null,"type":"education","lineage":["https://openalex.org/I4400009020"]},{"id":"https://openalex.org/I90023481","display_name":"National Institute of Information and Communications Technology","ror":"https://ror.org/016bgq349","country_code":"JP","type":"facility","lineage":["https://openalex.org/I90023481"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Minh Vu","raw_affiliation_strings":["Department of Information and Communications Engineering, Institute of Science Tokyo, Yokohama, Japan"],"affiliations":[{"raw_affiliation_string":"Department of Information and Communications Engineering, Institute of Science Tokyo, Yokohama, Japan","institution_ids":["https://openalex.org/I90023481","https://openalex.org/I4400009020"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5042922973","display_name":"Konstantinos Slavakis","orcid":"https://orcid.org/0000-0002-3370-3154"},"institutions":[{"id":"https://openalex.org/I90023481","display_name":"National Institute of Information and Communications Technology","ror":"https://ror.org/016bgq349","country_code":"JP","type":"facility","lineage":["https://openalex.org/I90023481"]},{"id":"https://openalex.org/I4400009020","display_name":"Institute of Science Tokyo","ror":"https://ror.org/05dqf9946","country_code":null,"type":"education","lineage":["https://openalex.org/I4400009020"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Konstantinos Slavakis","raw_affiliation_strings":["Department of Information and Communications Engineering, Institute of Science Tokyo, Yokohama, Japan"],"affiliations":[{"raw_affiliation_string":"Department of Information and Communications Engineering, Institute of Science Tokyo, Yokohama, Japan","institution_ids":["https://openalex.org/I90023481","https://openalex.org/I4400009020"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5115444776"],"corresponding_institution_ids":["https://openalex.org/I4400009020","https://openalex.org/I90023481"],"apc_list":null,"apc_paid":null,"fwci":1.9133,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.85092917,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"72","issue":null,"first_page":"5644","last_page":"5658"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11233","display_name":"Advanced Adaptive Filtering Techniques","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T11233","display_name":"Advanced Adaptive Filtering Techniques","score":0.9998999834060669,"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/T11052","display_name":"Energy Load and Power Forecasting","score":0.9929999709129333,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"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/T12794","display_name":"Adaptive Dynamic Programming Control","score":0.9843999743461609,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/reinforcement-learning","display_name":"Reinforcement learning","score":0.7823662757873535},{"id":"https://openalex.org/keywords/nonparametric-statistics","display_name":"Nonparametric statistics","score":0.689696192741394},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6576176881790161},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5320039391517639},{"id":"https://openalex.org/keywords/adaptive-filter","display_name":"Adaptive filter","score":0.45824524760246277},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.412309467792511},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3687586188316345},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2688443064689636},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.24659094214439392},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.21081215143203735}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.7823662757873535},{"id":"https://openalex.org/C102366305","wikidata":"https://www.wikidata.org/wiki/Q1097688","display_name":"Nonparametric statistics","level":2,"score":0.689696192741394},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6576176881790161},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5320039391517639},{"id":"https://openalex.org/C102248274","wikidata":"https://www.wikidata.org/wiki/Q168388","display_name":"Adaptive filter","level":2,"score":0.45824524760246277},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.412309467792511},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3687586188316345},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2688443064689636},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.24659094214439392},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.21081215143203735}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tsp.2024.3505266","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2024.3505266","pdf_url":null,"source":{"id":"https://openalex.org/S168680287","display_name":"IEEE Transactions on Signal Processing","issn_l":"1053-587X","issn":["1053-587X","1941-0476"],"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 Signal Processing","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":59,"referenced_works":["https://openalex.org/W368469426","https://openalex.org/W601863383","https://openalex.org/W1002758560","https://openalex.org/W1484867920","https://openalex.org/W1507222174","https://openalex.org/W1518539242","https://openalex.org/W1540586255","https://openalex.org/W1560724230","https://openalex.org/W1583497301","https://openalex.org/W1835716857","https://openalex.org/W1986280275","https://openalex.org/W1991877032","https://openalex.org/W1996124770","https://openalex.org/W2014914755","https://openalex.org/W2029634950","https://openalex.org/W2040766536","https://openalex.org/W2055576996","https://openalex.org/W2072931156","https://openalex.org/W2076005979","https://openalex.org/W2107221565","https://openalex.org/W2118556122","https://openalex.org/W2127805491","https://openalex.org/W2132351269","https://openalex.org/W2136409657","https://openalex.org/W2137312721","https://openalex.org/W2139418546","https://openalex.org/W2146641075","https://openalex.org/W2147839652","https://openalex.org/W2148024708","https://openalex.org/W2165218755","https://openalex.org/W2168359464","https://openalex.org/W2170629983","https://openalex.org/W2195535662","https://openalex.org/W2586680856","https://openalex.org/W2588821529","https://openalex.org/W2746553466","https://openalex.org/W2962847657","https://openalex.org/W2963289483","https://openalex.org/W3020075106","https://openalex.org/W3041202696","https://openalex.org/W3114895984","https://openalex.org/W4205326910","https://openalex.org/W4205987271","https://openalex.org/W4213251304","https://openalex.org/W4229650096","https://openalex.org/W4230058301","https://openalex.org/W4239240501","https://openalex.org/W4245296547","https://openalex.org/W4289287180","https://openalex.org/W4372262740","https://openalex.org/W6638822454","https://openalex.org/W6674428451","https://openalex.org/W6677089629","https://openalex.org/W6680315907","https://openalex.org/W6681302627","https://openalex.org/W6685993434","https://openalex.org/W6687681856","https://openalex.org/W6704979919","https://openalex.org/W6727147046"],"related_works":["https://openalex.org/W4243114048","https://openalex.org/W2529605301","https://openalex.org/W4237896776","https://openalex.org/W4231665652","https://openalex.org/W1837630526","https://openalex.org/W2000242494","https://openalex.org/W2335589441","https://openalex.org/W4296826658","https://openalex.org/W1979697693","https://openalex.org/W2164312800"],"abstract_inverted_index":{"This":[0],"paper":[1,99],"designs":[2],"novel":[3,139],"nonparametric":[4,40],"Bellman":[5,113],"mappings":[6,19,133],"in":[7,147,184,197],"reproducing":[8],"kernel":[9],"Hilbert":[10],"spaces":[11],"(RKHSs)":[12],"for":[13,62],"reinforcement":[14],"learning":[15],"(RL).":[16],"The":[17,98],"proposed":[18,112,132,207],"benefit":[20],"from":[21],"the":[22,32,35,66,107,111,131,142,157,160,177,185,200,202,206],"rich":[23],"approximating":[24],"properties":[25],"of":[26,34,48,68,110,120,144,159,199,205],"RKHSs,":[27],"adopt":[28],"no":[29,43,153,163],"assumptions":[30],"on":[31,45,156,193],"statistics":[33,158],"data":[36,74,195],"owing":[37],"to":[38,90,105,136,141,171],"their":[39],"nature,":[41],"require":[42],"knowledge":[44],"transition":[46],"probabilities":[47],"Markov":[49],"decision":[50],"processes,":[51],"and":[52,85,115,162,212],"may":[53],"operate":[54],"without":[55],"any":[56],"training":[57,164],"data.":[58],"Moreover,":[59],"they":[60],"allow":[61],"sampling":[63],"on-the-fly":[64],"via":[65,75],"design":[67,106],"trajectory":[69],"samples,":[70],"re-use":[71],"past":[72],"test":[73],"experience":[76],"replay,":[77],"effect":[78],"dimensionality":[79],"reduction":[80],"by":[81],"random":[82],"Fourier":[83],"features,":[84],"enable":[86],"computationally":[87],"lightweight":[88],"operations":[89],"fit":[91],"into":[92],"efficient":[93],"online":[94],"or":[95],"time-adaptive":[96],"learning.":[97],"offers":[100],"also":[101],"a":[102,138,166],"variational":[103],"framework":[104],"free":[108],"parameters":[109,122],"mappings,":[114],"shows":[116],"that":[117],"appropriate":[118],"choices":[119],"those":[121],"yield":[123],"several":[124,210],"popular":[125],"Bellman-mapping":[126],"designs.":[127],"As":[128],"an":[129],"application,":[130],"are":[134],"employed":[135],"offer":[137],"solution":[140,208],"problem":[143],"countering":[145],"outliers":[146,161],"adaptive":[148],"filtering.":[149],"More":[150],"specifically,":[151],"with":[152],"prior":[154],"information":[155],"data,":[165],"policy-iteration":[167],"algorithm":[168],"is":[169],"introduced":[170],"select":[172],"online,":[173],"per":[174],"time":[175],"instance,":[176],"\u201coptimal\u201d":[178],"coefficient":[179],"<inline-formula":[180],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[181,187],"xmlns:xlink=\"http://www.w3.org/1999/xlink\"><tex-math":[182,188],"notation=\"LaTeX\">$p$</tex-math></inline-formula>":[183],"least-mean-<inline-formula":[186],"notation=\"LaTeX\">$p$</tex-math></inline-formula>-power-error":[189],"method.":[190],"Numerical":[191],"tests":[192],"synthetic":[194],"showcase,":[196],"most":[198],"cases,":[201],"superior":[203],"performance":[204],"over":[209],"RL":[211],"non-RL":[213],"schemes.":[214]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":3}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}