{"id":"https://openalex.org/W3032061229","doi":"https://doi.org/10.1109/lsp.2020.2998361","title":"Variational Denoising Autoencoders and Least-Squares Policy Iteration for Statistical Dialogue Managers","display_name":"Variational Denoising Autoencoders and Least-Squares Policy Iteration for Statistical Dialogue Managers","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3032061229","doi":"https://doi.org/10.1109/lsp.2020.2998361","mag":"3032061229"},"language":"en","primary_location":{"id":"doi:10.1109/lsp.2020.2998361","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2020.2998361","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"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 Signal Processing Letters","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/A5031538820","display_name":"Vassilios Diakoloukas","orcid":"https://orcid.org/0000-0002-1030-2892"},"institutions":[{"id":"https://openalex.org/I55741626","display_name":"Technical University of Crete","ror":"https://ror.org/03f8bz564","country_code":"GR","type":"education","lineage":["https://openalex.org/I55741626"]}],"countries":["GR"],"is_corresponding":true,"raw_author_name":"Vassilios Diakoloukas","raw_affiliation_strings":["School of Electrical and Computer Engineering, Technical University of Crete, Chania, Greece"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Computer Engineering, Technical University of Crete, Chania, Greece","institution_ids":["https://openalex.org/I55741626"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064630658","display_name":"Fotios Lygerakis","orcid":"https://orcid.org/0000-0001-8044-3511"},"institutions":[{"id":"https://openalex.org/I55741626","display_name":"Technical University of Crete","ror":"https://ror.org/03f8bz564","country_code":"GR","type":"education","lineage":["https://openalex.org/I55741626"]},{"id":"https://openalex.org/I4210143477","display_name":"Toshiba (United Kingdom)","ror":"https://ror.org/054hmd463","country_code":"GB","type":"company","lineage":["https://openalex.org/I1292669757","https://openalex.org/I4210143477"]}],"countries":["GB","GR"],"is_corresponding":false,"raw_author_name":"Fotios Lygerakis","raw_affiliation_strings":["School of Electrical and Computer Engineering, Technical University of Crete, Chania, Greece","Toshiba Research Europe Limited, Cambridge, U.K"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Computer Engineering, Technical University of Crete, Chania, Greece","institution_ids":["https://openalex.org/I55741626"]},{"raw_affiliation_string":"Toshiba Research Europe Limited, Cambridge, U.K","institution_ids":["https://openalex.org/I4210143477"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084693234","display_name":"Michail G. Lagoudakis","orcid":"https://orcid.org/0000-0003-2803-3755"},"institutions":[{"id":"https://openalex.org/I55741626","display_name":"Technical University of Crete","ror":"https://ror.org/03f8bz564","country_code":"GR","type":"education","lineage":["https://openalex.org/I55741626"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Michail G. Lagoudakis","raw_affiliation_strings":["School of Electrical and Computer Engineering, Technical University of Crete, Chania, Greece"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Computer Engineering, Technical University of Crete, Chania, Greece","institution_ids":["https://openalex.org/I55741626"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5031329337","display_name":"Margarita Kotti","orcid":"https://orcid.org/0000-0003-4212-7037"},"institutions":[{"id":"https://openalex.org/I4210143477","display_name":"Toshiba (United Kingdom)","ror":"https://ror.org/054hmd463","country_code":"GB","type":"company","lineage":["https://openalex.org/I1292669757","https://openalex.org/I4210143477"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Margarita Kotti","raw_affiliation_strings":["Artificial Intelligence, Deloitte, London, U.K","Toshiba Research Europe Limited, Cambridge, U.K"],"affiliations":[{"raw_affiliation_string":"Artificial Intelligence, Deloitte, London, U.K","institution_ids":[]},{"raw_affiliation_string":"Toshiba Research Europe Limited, Cambridge, U.K","institution_ids":["https://openalex.org/I4210143477"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5031538820"],"corresponding_institution_ids":["https://openalex.org/I55741626"],"apc_list":null,"apc_paid":null,"fwci":0.6628,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.75382449,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"27","issue":null,"first_page":"960","last_page":"964"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12031","display_name":"Speech and dialogue systems","score":1.0,"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/T12031","display_name":"Speech and dialogue systems","score":1.0,"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/T10201","display_name":"Speech Recognition and Synthesis","score":0.9980999827384949,"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/T10028","display_name":"Topic Modeling","score":0.9965000152587891,"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/reinforcement-learning","display_name":"Reinforcement learning","score":0.7337766885757446},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7133023142814636},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.6905943155288696},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.6401063203811646},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5783995389938354},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.564450204372406},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.4795410633087158},{"id":"https://openalex.org/keywords/scheme","display_name":"Scheme (mathematics)","score":0.4456935226917267},{"id":"https://openalex.org/keywords/least-squares-function-approximation","display_name":"Least-squares function approximation","score":0.442937433719635},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3657519817352295},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3612256944179535},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3585848808288574},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1838245689868927},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.10356801748275757}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.7337766885757446},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7133023142814636},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.6905943155288696},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.6401063203811646},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5783995389938354},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.564450204372406},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.4795410633087158},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.4456935226917267},{"id":"https://openalex.org/C9936470","wikidata":"https://www.wikidata.org/wiki/Q6510405","display_name":"Least-squares function approximation","level":3,"score":0.442937433719635},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3657519817352295},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3612256944179535},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3585848808288574},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1838245689868927},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.10356801748275757},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/lsp.2020.2998361","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2020.2998361","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"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 Signal Processing Letters","raw_type":"journal-article"},{"id":"pmh:oai:spiral.imperial.ac.uk:10044/1/80679","is_oa":false,"landing_page_url":"http://hdl.handle.net/10044/1/80679","pdf_url":null,"source":{"id":"https://openalex.org/S4306401396","display_name":"Spiral (Imperial College London)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I47508984","host_organization_name":"Imperial College London","host_organization_lineage":["https://openalex.org/I47508984"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"964","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":39,"referenced_works":["https://openalex.org/W86816279","https://openalex.org/W1211946649","https://openalex.org/W1591706642","https://openalex.org/W1757796397","https://openalex.org/W1959608418","https://openalex.org/W1975244201","https://openalex.org/W2142831953","https://openalex.org/W2145094598","https://openalex.org/W2154740693","https://openalex.org/W2156974606","https://openalex.org/W2250262342","https://openalex.org/W2438667436","https://openalex.org/W2586680856","https://openalex.org/W2739936944","https://openalex.org/W2771236725","https://openalex.org/W2772217324","https://openalex.org/W2889034239","https://openalex.org/W2889165300","https://openalex.org/W2946824041","https://openalex.org/W2950953090","https://openalex.org/W2962883855","https://openalex.org/W2963306198","https://openalex.org/W2963993502","https://openalex.org/W2964044380","https://openalex.org/W2997574889","https://openalex.org/W3007437568","https://openalex.org/W4285719527","https://openalex.org/W4294342177","https://openalex.org/W4297806413","https://openalex.org/W4298857966","https://openalex.org/W4391602018","https://openalex.org/W6603545158","https://openalex.org/W6623987585","https://openalex.org/W6628025142","https://openalex.org/W6635590879","https://openalex.org/W6637967152","https://openalex.org/W6640963894","https://openalex.org/W6681096077","https://openalex.org/W6746188011"],"related_works":["https://openalex.org/W4362501864","https://openalex.org/W4306904969","https://openalex.org/W4380318855","https://openalex.org/W2138720691","https://openalex.org/W2031695474","https://openalex.org/W2389214306","https://openalex.org/W2586732548","https://openalex.org/W3049728571","https://openalex.org/W20361778","https://openalex.org/W2024136090"],"abstract_inverted_index":{"The":[0,94],"use":[1],"of":[2,38,47],"Reinforcement":[3],"Learning":[4],"(RL)":[5],"approaches":[6,40],"for":[7,16],"dialogue":[8,17,29,84],"policy":[9],"optimization":[10],"has":[11],"been":[12,23],"the":[13,45,70,105],"new":[14],"trend":[15],"management":[18],"systems.":[19],"Several":[20],"methods":[21],"have":[22],"proposed,":[24],"which":[25,78,102],"are":[26],"trained":[27,80],"on":[28,69,81],"data":[30],"to":[31,51],"provide":[32],"optimal":[33],"system":[34],"response.":[35],"However,":[36],"most":[37],"these":[39,61],"exhibit":[41],"performance":[42,57],"degradation":[43],"in":[44,109],"presence":[46],"noise,":[48],"poor":[49],"scalability":[50],"other":[52],"domains,":[53],"as":[54,56],"well":[55],"instabilities.":[58],"To":[59],"overcome":[60],"problems,":[62],"we":[63],"propose":[64],"a":[65],"novel":[66],"approach":[67],"based":[68],"incremental,":[71],"sample-efficient":[72],"Least-Squares":[73],"Policy":[74],"Iteration":[75],"(LSPI)":[76],"algorithm,":[77],"is":[79],"compact,":[82],"fixed-size":[83],"state":[85],"encodings,":[86],"obtained":[87],"from":[88],"deep":[89],"Variational":[90],"Denoising":[91],"Autoencoders":[92],"(VDAE).":[93],"proposed":[95],"scheme":[96],"exhibits":[97],"stable":[98],"and":[99],"noise-robust":[100],"performance,":[101],"significantly":[103],"outperforms":[104],"current":[106],"state-of-the-art,":[107],"even":[108],"mismatched":[110],"noise":[111],"environments.":[112]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2020,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
