{"id":"https://openalex.org/W3201291877","doi":"https://doi.org/10.1080/00401706.2022.2146755","title":"Dynamic Mixture of Experts Models for Online Prediction","display_name":"Dynamic Mixture of Experts Models for Online Prediction","publication_year":2022,"publication_date":"2022-11-17","ids":{"openalex":"https://openalex.org/W3201291877","doi":"https://doi.org/10.1080/00401706.2022.2146755","mag":"3201291877"},"language":"en","primary_location":{"id":"doi:10.1080/00401706.2022.2146755","is_oa":false,"landing_page_url":"https://doi.org/10.1080/00401706.2022.2146755","pdf_url":null,"source":{"id":"https://openalex.org/S985303","display_name":"Technometrics","issn_l":"0040-1706","issn":["0040-1706","1537-2723"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547","https://openalex.org/P4310320449"],"host_organization_lineage_names":["Taylor & Francis","Informa"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Technometrics","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/A5061121696","display_name":"Parfait Munezero","orcid":"https://orcid.org/0000-0002-3902-3846"},"institutions":[{"id":"https://openalex.org/I1279596006","display_name":"Statistics Sweden","ror":"https://ror.org/05x7wz523","country_code":"SE","type":"government","lineage":["https://openalex.org/I1279596006"]},{"id":"https://openalex.org/I1306339040","display_name":"Ericsson (Sweden)","ror":"https://ror.org/05a7rhx54","country_code":"SE","type":"company","lineage":["https://openalex.org/I1306339040"]},{"id":"https://openalex.org/I161593684","display_name":"Stockholm University","ror":"https://ror.org/05f0yaq80","country_code":"SE","type":"education","lineage":["https://openalex.org/I161593684"]}],"countries":["SE"],"is_corresponding":true,"raw_author_name":"Parfait Munezero","raw_affiliation_strings":["Data Insights Support Team, Ericsson, Stockholm, Sweden","Department of Statistics, Stockholm University, Stockholm, Sweden"],"raw_orcid":"https://orcid.org/0000-0002-3902-3846","affiliations":[{"raw_affiliation_string":"Data Insights Support Team, Ericsson, Stockholm, Sweden","institution_ids":["https://openalex.org/I1306339040"]},{"raw_affiliation_string":"Department of Statistics, Stockholm University, Stockholm, Sweden","institution_ids":["https://openalex.org/I1279596006","https://openalex.org/I161593684"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050445437","display_name":"Mattias Villani","orcid":"https://orcid.org/0000-0003-2786-2519"},"institutions":[{"id":"https://openalex.org/I102134673","display_name":"Link\u00f6ping University","ror":"https://ror.org/05ynxx418","country_code":"SE","type":"education","lineage":["https://openalex.org/I102134673"]},{"id":"https://openalex.org/I1279596006","display_name":"Statistics Sweden","ror":"https://ror.org/05x7wz523","country_code":"SE","type":"government","lineage":["https://openalex.org/I1279596006"]},{"id":"https://openalex.org/I161593684","display_name":"Stockholm University","ror":"https://ror.org/05f0yaq80","country_code":"SE","type":"education","lineage":["https://openalex.org/I161593684"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Mattias Villani","raw_affiliation_strings":["Department of Computer and Information Science, Link\u00f6ping University, Link\u00f6ping, Sweden","Department of Statistics, Stockholm University, Stockholm, Sweden"],"raw_orcid":"https://orcid.org/0000-0003-2786-2519","affiliations":[{"raw_affiliation_string":"Department of Computer and Information Science, Link\u00f6ping University, Link\u00f6ping, Sweden","institution_ids":["https://openalex.org/I102134673"]},{"raw_affiliation_string":"Department of Statistics, Stockholm University, Stockholm, Sweden","institution_ids":["https://openalex.org/I1279596006","https://openalex.org/I161593684"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5051693933","display_name":"Robert Kohn","orcid":"https://orcid.org/0000-0002-3733-1474"},"institutions":[{"id":"https://openalex.org/I31746571","display_name":"UNSW Sydney","ror":"https://ror.org/03r8z3t63","country_code":"AU","type":"education","lineage":["https://openalex.org/I31746571"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Robert Kohn","raw_affiliation_strings":["UNSW Business School, University of New South Wales, Sydney, Australia"],"raw_orcid":"https://orcid.org/0000-0002-3733-1474","affiliations":[{"raw_affiliation_string":"UNSW Business School, University of New South Wales, Sydney, Australia","institution_ids":["https://openalex.org/I31746571"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5061121696"],"corresponding_institution_ids":["https://openalex.org/I1279596006","https://openalex.org/I1306339040","https://openalex.org/I161593684"],"apc_list":null,"apc_paid":null,"fwci":0.2322,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.57179792,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"65","issue":"2","first_page":"257","last_page":"268"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9991999864578247,"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/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9991999864578247,"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/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.996999979019165,"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/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.9901999831199646,"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/mixture-model","display_name":"Mixture model","score":0.6892202496528625},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6761071681976318},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6252450346946716},{"id":"https://openalex.org/keywords/covariate","display_name":"Covariate","score":0.515063464641571},{"id":"https://openalex.org/keywords/parameterized-complexity","display_name":"Parameterized complexity","score":0.5136322379112244},{"id":"https://openalex.org/keywords/software","display_name":"Software","score":0.4638870358467102},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4610655903816223},{"id":"https://openalex.org/keywords/mixture-distribution","display_name":"Mixture distribution","score":0.44841259717941284},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4139552712440491},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.32360219955444336},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.31920263171195984},{"id":"https://openalex.org/keywords/random-variable","display_name":"Random variable","score":0.278409481048584},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2435835897922516},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.19917955994606018}],"concepts":[{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.6892202496528625},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6761071681976318},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6252450346946716},{"id":"https://openalex.org/C119043178","wikidata":"https://www.wikidata.org/wiki/Q320723","display_name":"Covariate","level":2,"score":0.515063464641571},{"id":"https://openalex.org/C165464430","wikidata":"https://www.wikidata.org/wiki/Q1570441","display_name":"Parameterized complexity","level":2,"score":0.5136322379112244},{"id":"https://openalex.org/C2777904410","wikidata":"https://www.wikidata.org/wiki/Q7397","display_name":"Software","level":2,"score":0.4638870358467102},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4610655903816223},{"id":"https://openalex.org/C56672385","wikidata":"https://www.wikidata.org/wiki/Q17157111","display_name":"Mixture distribution","level":3,"score":0.44841259717941284},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4139552712440491},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.32360219955444336},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.31920263171195984},{"id":"https://openalex.org/C122123141","wikidata":"https://www.wikidata.org/wiki/Q176623","display_name":"Random variable","level":2,"score":0.278409481048584},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2435835897922516},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.19917955994606018},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/00401706.2022.2146755","is_oa":false,"landing_page_url":"https://doi.org/10.1080/00401706.2022.2146755","pdf_url":null,"source":{"id":"https://openalex.org/S985303","display_name":"Technometrics","issn_l":"0040-1706","issn":["0040-1706","1537-2723"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547","https://openalex.org/P4310320449"],"host_organization_lineage_names":["Taylor & Francis","Informa"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Technometrics","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.41999998688697815,"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":67,"referenced_works":["https://openalex.org/W68616770","https://openalex.org/W143236119","https://openalex.org/W214193251","https://openalex.org/W1483307070","https://openalex.org/W1501586228","https://openalex.org/W1520053542","https://openalex.org/W1601795611","https://openalex.org/W1663973292","https://openalex.org/W1813877430","https://openalex.org/W1876120984","https://openalex.org/W1912628714","https://openalex.org/W1972144663","https://openalex.org/W1974180009","https://openalex.org/W1980792219","https://openalex.org/W1981276685","https://openalex.org/W1999229317","https://openalex.org/W2009225465","https://openalex.org/W2011696639","https://openalex.org/W2024589952","https://openalex.org/W2025653905","https://openalex.org/W2026999222","https://openalex.org/W2027628336","https://openalex.org/W2038885294","https://openalex.org/W2045019767","https://openalex.org/W2049633694","https://openalex.org/W2057565703","https://openalex.org/W2057964179","https://openalex.org/W2059631514","https://openalex.org/W2060624359","https://openalex.org/W2061929874","https://openalex.org/W2062464420","https://openalex.org/W2063188271","https://openalex.org/W2063478550","https://openalex.org/W2064119066","https://openalex.org/W2064480843","https://openalex.org/W2068238590","https://openalex.org/W2081741802","https://openalex.org/W2082542916","https://openalex.org/W2087101057","https://openalex.org/W2090415144","https://openalex.org/W2098613108","https://openalex.org/W2098949458","https://openalex.org/W2099339563","https://openalex.org/W2111787305","https://openalex.org/W2111809489","https://openalex.org/W2113884043","https://openalex.org/W2119786140","https://openalex.org/W2126736494","https://openalex.org/W2130363011","https://openalex.org/W2131598171","https://openalex.org/W2137307912","https://openalex.org/W2147357149","https://openalex.org/W2165609874","https://openalex.org/W2183241504","https://openalex.org/W2211895605","https://openalex.org/W2468546872","https://openalex.org/W2509991828","https://openalex.org/W2541774717","https://openalex.org/W2809666375","https://openalex.org/W2906023557","https://openalex.org/W2999905431","https://openalex.org/W3099828905","https://openalex.org/W3123049573","https://openalex.org/W3151826159","https://openalex.org/W3202069324","https://openalex.org/W4230472026","https://openalex.org/W4308951891"],"related_works":["https://openalex.org/W4287816759","https://openalex.org/W2198732287","https://openalex.org/W2598185551","https://openalex.org/W2044981176","https://openalex.org/W2017090935","https://openalex.org/W2116212858","https://openalex.org/W2032556230","https://openalex.org/W3119669586","https://openalex.org/W2372918136","https://openalex.org/W2803473765"],"abstract_inverted_index":{"A":[0],"mixture":[1,14,20,26,37,58],"of":[2,8,15,27,59,106,113],"experts":[3,28,60],"models":[4,17,61],"the":[5,24,32,36,40,88,103,111,114,124],"conditional":[6],"density":[7],"a":[9,13,66,76,94,132],"response":[10],"variable":[11],"using":[12],"regression":[16],"with":[18,99],"covariate-dependent":[19],"weights.":[21],"We":[22,64,109],"extend":[23],"finite":[25],"model":[29],"by":[30,46],"allowing":[31],"parameters":[33,54],"in":[34,44,55,131],"both":[35],"components":[38],"and":[39,87,119],"weights":[41],"to":[42,127],"evolve":[43],"time":[45],"following":[47],"random":[48],"walk":[49],"processes.":[50],"Inference":[51],"for":[52,71,97],"time-varying":[53,100],"richly":[56],"parameterized":[57],"is":[62,126],"challenging.":[63],"propose":[65],"sequential":[67],"Monte":[68],"Carlo":[69],"algorithm":[70],"online":[72],"inference":[73],"based":[74],"on":[75,81,116,120],"tailored":[77],"proposal":[78],"distribution":[79],"built":[80],"ideas":[82],"from":[83],"linear":[84],"Bayes":[85],"methods":[86],"EM":[89],"algorithm.":[90],"The":[91],"method":[92,115],"gives":[93],"unified":[95],"treatment":[96],"mixtures":[98],"parameters,":[101],"including":[102],"special":[104],"case":[105],"static":[107],"parameters.":[108],"assess":[110],"properties":[112],"simulated":[117],"data":[118,122],"industrial":[121],"where":[123],"aim":[125],"predict":[128],"software":[129,136],"faults":[130],"continuously":[133],"upgraded":[134],"large-scale":[135],"project.":[137]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2}],"updated_date":"2026-08-15T07:11:24.734988","created_date":"2025-10-10T00:00:00"}
