{"id":"https://openalex.org/W2292930426","doi":"https://doi.org/10.1109/asru.2015.7404776","title":"Spectral learning with non negative probabilities for finite state automaton","display_name":"Spectral learning with non negative probabilities for finite state automaton","publication_year":2015,"publication_date":"2015-12-01","ids":{"openalex":"https://openalex.org/W2292930426","doi":"https://doi.org/10.1109/asru.2015.7404776","mag":"2292930426"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/asru.2015.7404776","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},"type":"article","type_crossref":"proceedings-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/A5080320000","display_name":"Hadrien Glaude","orcid":null},"institutions":[{"id":"https://openalex.org/I2279609970","display_name":"Universit\u00e9 de Lille","ror":"https://ror.org/02kzqn938","country_code":"FR","type":"education","lineage":["https://openalex.org/I2279609970"]},{"id":"https://openalex.org/I4210140930","display_name":"Thales (France)","ror":"https://ror.org/04emwm605","country_code":"FR","type":"company","lineage":["https://openalex.org/I4210140930"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Hadrien Glaude","raw_affiliation_strings":["Thales Airborne Systems, France","Univ. Lille, CRIStAL, UMR 9189, SequeL Team, France"],"affiliations":[{"raw_affiliation_string":"Univ. Lille, CRIStAL, UMR 9189, SequeL Team, France","institution_ids":["https://openalex.org/I2279609970"]},{"raw_affiliation_string":"Thales Airborne Systems, France","institution_ids":["https://openalex.org/I4210140930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110126636","display_name":"Cyrille Enderli","orcid":null},"institutions":[{"id":"https://openalex.org/I4210140930","display_name":"Thales (France)","ror":"https://ror.org/04emwm605","country_code":"FR","type":"company","lineage":["https://openalex.org/I4210140930"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Cyrille Enderli","raw_affiliation_strings":["Thales Airborne Systems, France"],"affiliations":[{"raw_affiliation_string":"Thales Airborne Systems, France","institution_ids":["https://openalex.org/I4210140930"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5065100569","display_name":"Olivier Pietquin","orcid":"https://orcid.org/0000-0002-5386-465X"},"institutions":[{"id":"https://openalex.org/I2279609970","display_name":"Universit\u00e9 de Lille","ror":"https://ror.org/02kzqn938","country_code":"FR","type":"education","lineage":["https://openalex.org/I2279609970"]},{"id":"https://openalex.org/I185839726","display_name":"Institut Universitaire de France","ror":"https://ror.org/055khg266","country_code":"FR","type":"education","lineage":["https://openalex.org/I185839726"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Olivier Pietquin","raw_affiliation_strings":["Institut Universitaire de France (IUF)","Univ. Lille, CRIStAL, UMR 9189, SequeL Team, France"],"affiliations":[{"raw_affiliation_string":"Univ. Lille, CRIStAL, UMR 9189, SequeL Team, France","institution_ids":["https://openalex.org/I2279609970"]},{"raw_affiliation_string":"Institut Universitaire de France (IUF)","institution_ids":["https://openalex.org/I185839726"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.136,"has_fulltext":true,"fulltext_origin":"ngrams","cited_by_count":1,"citation_normalized_percentile":{"value":0.198336,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":66,"max":73},"biblio":{"volume":null,"issue":null,"first_page":"71","last_page":"77"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T12072","display_name":"Machine Learning and Algorithms","score":0.9992,"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":0.9992,"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":0.9991,"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/T11269","display_name":"Algorithms and Data Compression","score":0.9988,"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/initialization","display_name":"Initialization","score":0.7676228},{"id":"https://openalex.org/keywords/probabilistic-automaton","display_name":"Probabilistic automaton","score":0.54527175},{"id":"https://openalex.org/keywords/learning-automata","display_name":"Learning Automata","score":0.41602492}],"concepts":[{"id":"https://openalex.org/C114466953","wikidata":"https://www.wikidata.org/wiki/Q6034165","display_name":"Initialization","level":2,"score":0.7676228},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7306917},{"id":"https://openalex.org/C182081679","wikidata":"https://www.wikidata.org/wiki/Q1275153","display_name":"Expectation\u2013maximization algorithm","level":3,"score":0.64085996},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.5887379},{"id":"https://openalex.org/C174784677","wikidata":"https://www.wikidata.org/wiki/Q176567","display_name":"Probabilistic automaton","level":3,"score":0.54527175},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.52055794},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.5130745},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.45565605},{"id":"https://openalex.org/C167822520","wikidata":"https://www.wikidata.org/wiki/Q176452","display_name":"Finite-state machine","level":2,"score":0.44719929},{"id":"https://openalex.org/C112505250","wikidata":"https://www.wikidata.org/wiki/Q787116","display_name":"Automaton","level":2,"score":0.44602716},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4324739},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.4207423},{"id":"https://openalex.org/C2776807809","wikidata":"https://www.wikidata.org/wiki/Q6510160","display_name":"Learning automata","level":3,"score":0.41602492},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33809316},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.19610521},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.10771194},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/asru.2015.7404776","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality education","id":"https://metadata.un.org/sdg/4","score":0.66}],"grants":[],"datasets":[],"versions":[],"referenced_works_count":24,"referenced_works":["https://openalex.org/W150331267","https://openalex.org/W1560796813","https://openalex.org/W1570013475","https://openalex.org/W1587826772","https://openalex.org/W1700863064","https://openalex.org/W1726002263","https://openalex.org/W1854811422","https://openalex.org/W196214544","https://openalex.org/W2001096515","https://openalex.org/W2001179000","https://openalex.org/W2051028214","https://openalex.org/W2059144133","https://openalex.org/W2105724942","https://openalex.org/W2112861996","https://openalex.org/W2117421927","https://openalex.org/W2125529971","https://openalex.org/W2125838338","https://openalex.org/W2131537383","https://openalex.org/W2131930295","https://openalex.org/W2140351241","https://openalex.org/W2159039874","https://openalex.org/W2476025067","https://openalex.org/W2950741027","https://openalex.org/W2997643781"],"related_works":["https://openalex.org/W97133087","https://openalex.org/W4248402004","https://openalex.org/W3200605392","https://openalex.org/W3090561264","https://openalex.org/W2803580888","https://openalex.org/W2097847787","https://openalex.org/W2078124810","https://openalex.org/W2041758614","https://openalex.org/W1552686964","https://openalex.org/W1539249290"],"abstract_inverted_index":{"Probabilistic":[0,4],"Finite":[1,5],"Automaton":[2],"(PFA),":[3],"State":[6],"Transducers":[7],"(PFST)":[8],"and":[9,25,85,115,159],"Hidden":[10],"Markov":[11],"Models":[12],"(HMM)":[13],"are":[14,80,94],"widely":[15],"used":[16],"in":[17,182],"Automatic":[18],"Speech":[19,28],"Recognition":[20],"(ASR),":[21],"Text-to-Speech":[22],"(TTS)":[23],"systems":[24],"Part":[26],"Of":[27],"(POS)":[29],"tagging":[30],"for":[31],"language":[32],"modeling.":[33],"Traditionally,":[34],"unsupervised":[35],"learning":[36,59],"of":[37,57,65,82,141],"these":[38],"latent":[39],"variable":[40],"models":[41,93,142],"is":[42],"done":[43],"by":[44],"Expectation-Maximization":[45],"(EM)-like":[46],"algorithms,":[47],"as":[48,120,173,175,186],"the":[49,156,176],"Baum-Welch":[50,177],"algorithm.":[51],"In":[52,75,126],"a":[53,131,138],"recent":[54],"alternative":[55],"line":[56],"work,":[58],"algorithms":[60],"based":[61],"on":[62,152],"spectral":[63,133,171],"properties":[64],"some":[66],"low":[67],"order":[68],"moments":[69],"matrices":[70],"or":[71],"tensors":[72],"were":[73],"proposed.":[74],"comparison":[76],"to":[77,97,110,118,123,136,144,184,191],"EM,":[78],"they":[79],"orders":[81],"magnitude":[83],"faster":[84],"come":[86],"with":[87,179],"theoretical":[88],"convergence":[89],"guarantees.":[90],"However,":[91],"returned":[92],"not":[95,108],"ensured":[96],"compute":[98],"proper":[99,146],"distributions.":[100,147],"They":[101],"often":[102],"return":[103,145],"negative":[104],"values":[105],"that":[106,167],"do":[107],"sum":[109],"one,":[111],"limiting":[112],"their":[113],"applicability":[114],"preventing":[116],"them":[117],"serve":[119,185],"an":[121,187],"initialization":[122,189],"EM-like":[124,192],"algorithms.":[125,193],"this":[127],"paper,":[128],"we":[129],"propose":[130],"new":[132],"algorithm":[134,178],"able":[135],"learn":[137],"large":[139],"range":[140],"constrained":[143],"We":[148],"assess":[149],"its":[150],"performances":[151],"synthetic":[153],"problems":[154],"from":[155,163],"PAutomaC":[157],"challenge":[158],"real":[160],"datasets":[161],"extracted":[162],"Wikipedia.":[164],"Experiments":[165],"show":[166],"it":[168],"outperforms":[169],"previous":[170],"approaches":[172],"well":[174],"random":[180],"restarts,":[181],"addition":[183],"efficient":[188],"step":[190]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W2292930426","counts_by_year":[{"year":2016,"cited_by_count":1}],"updated_date":"2024-12-09T20:00:30.248421","created_date":"2016-06-24"}