{"id":"https://openalex.org/W2566185378","doi":"https://doi.org/10.1109/dicta.2016.7796997","title":"A Simple Parallel EM Algorithm for Statistical Learning via Mixture Models","display_name":"A Simple Parallel EM Algorithm for Statistical Learning via Mixture Models","publication_year":2016,"publication_date":"2016-11-01","ids":{"openalex":"https://openalex.org/W2566185378","doi":"https://doi.org/10.1109/dicta.2016.7796997","mag":"2566185378"},"language":"en","primary_location":{"id":"doi:10.1109/dicta.2016.7796997","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dicta.2016.7796997","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 International Conference on Digital Image Computing: Techniques and Applications (DICTA)","raw_type":"proceedings-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/A5108094345","display_name":"Sharon Lee","orcid":null},"institutions":[{"id":"https://openalex.org/I165143802","display_name":"The University of Queensland","ror":"https://ror.org/00rqy9422","country_code":"AU","type":"education","lineage":["https://openalex.org/I165143802"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Sharon X. Lee","raw_affiliation_strings":["Dept. of Math., Univ. of Queensland, St. Lucia, QLD, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of Math., Univ. of Queensland, St. Lucia, QLD, Australia","institution_ids":["https://openalex.org/I165143802"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103129472","display_name":"Kaleb L. Leemaqz","orcid":"https://orcid.org/0000-0002-6391-135X"},"institutions":[{"id":"https://openalex.org/I165143802","display_name":"The University of Queensland","ror":"https://ror.org/00rqy9422","country_code":"AU","type":"education","lineage":["https://openalex.org/I165143802"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Kaleb L. Leemaqz","raw_affiliation_strings":["Dept. of Math., Univ. of Queensland, St. Lucia, QLD, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of Math., Univ. of Queensland, St. Lucia, QLD, Australia","institution_ids":["https://openalex.org/I165143802"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5057375178","display_name":"Geoffrey J. McLachlan","orcid":"https://orcid.org/0000-0002-5921-3145"},"institutions":[{"id":"https://openalex.org/I165143802","display_name":"The University of Queensland","ror":"https://ror.org/00rqy9422","country_code":"AU","type":"education","lineage":["https://openalex.org/I165143802"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Geoffrey J. McLachlan","raw_affiliation_strings":["Dept. of Math., Univ. of Queensland, St. Lucia, QLD, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of Math., Univ. of Queensland, St. Lucia, QLD, Australia","institution_ids":["https://openalex.org/I165143802"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I165143802"],"apc_list":null,"apc_paid":null,"fwci":1.3248,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.87963845,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"20","issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9909999966621399,"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/T10968","display_name":"Statistical Distribution Estimation and Applications","score":0.9904000163078308,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/expectation\u2013maximization-algorithm","display_name":"Expectation\u2013maximization algorithm","score":0.795732855796814},{"id":"https://openalex.org/keywords/skew","display_name":"Skew","score":0.7634470462799072},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7242591381072998},{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.6843676567077637},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5788625478744507},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.5181542634963989},{"id":"https://openalex.org/keywords/simple","display_name":"Simple (philosophy)","score":0.5087178349494934},{"id":"https://openalex.org/keywords/parametric-statistics","display_name":"Parametric statistics","score":0.4497404992580414},{"id":"https://openalex.org/keywords/maximum-likelihood","display_name":"Maximum likelihood","score":0.2612518072128296},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.19235840439796448},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.17557793855667114}],"concepts":[{"id":"https://openalex.org/C182081679","wikidata":"https://www.wikidata.org/wiki/Q1275153","display_name":"Expectation\u2013maximization algorithm","level":3,"score":0.795732855796814},{"id":"https://openalex.org/C43711488","wikidata":"https://www.wikidata.org/wiki/Q7534783","display_name":"Skew","level":2,"score":0.7634470462799072},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7242591381072998},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.6843676567077637},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5788625478744507},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.5181542634963989},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.5087178349494934},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.4497404992580414},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.2612518072128296},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.19235840439796448},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.17557793855667114},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/dicta.2016.7796997","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dicta.2016.7796997","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 International Conference on Digital Image Computing: Techniques and Applications (DICTA)","raw_type":"proceedings-article"},{"id":"pmh:oai:espace.library.uq.edu.au:UQ:415901","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4306402388","display_name":"Queensland's institutional digital repository (The University of Queensland)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I165143802","host_organization_name":"The University of Queensland","host_organization_lineage":["https://openalex.org/I165143802"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference Paper"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W306662213","https://openalex.org/W605692607","https://openalex.org/W619265607","https://openalex.org/W805531662","https://openalex.org/W1664060554","https://openalex.org/W1982914322","https://openalex.org/W1992558052","https://openalex.org/W2001619934","https://openalex.org/W2020158974","https://openalex.org/W2030061514","https://openalex.org/W2033076513","https://openalex.org/W2035886438","https://openalex.org/W2039615557","https://openalex.org/W2045254715","https://openalex.org/W2047555270","https://openalex.org/W2063034004","https://openalex.org/W2068686165","https://openalex.org/W2073984943","https://openalex.org/W2077321682","https://openalex.org/W2079256353","https://openalex.org/W2082503527","https://openalex.org/W2097446839","https://openalex.org/W2098439089","https://openalex.org/W2112493011","https://openalex.org/W2121529133","https://openalex.org/W2130878631","https://openalex.org/W2138924491","https://openalex.org/W2157321274","https://openalex.org/W2166698530","https://openalex.org/W2187120389","https://openalex.org/W2465581670","https://openalex.org/W2488678869","https://openalex.org/W2797746357","https://openalex.org/W2963540105","https://openalex.org/W2963879592","https://openalex.org/W3121736584","https://openalex.org/W4235169531","https://openalex.org/W4248463836","https://openalex.org/W4255932839","https://openalex.org/W4300956553","https://openalex.org/W6686622916"],"related_works":["https://openalex.org/W2473373438","https://openalex.org/W269711013","https://openalex.org/W2368486525","https://openalex.org/W2077224612","https://openalex.org/W2153481672","https://openalex.org/W2153238387","https://openalex.org/W84255947","https://openalex.org/W4312864369","https://openalex.org/W2014842417","https://openalex.org/W2891133681"],"abstract_inverted_index":{"Finite":[0],"mixture":[1,54,107,172,187],"models":[2,188],"have":[3],"been":[4],"widely":[5],"used":[6,186],"for":[7,66,85,102,116],"the":[8,21,28,35,38,42,49,53,57,60,68,99,103,111,114,119,139,164,183,190],"modelling":[9],"and":[10,63,121,151,195],"analysis":[11],"of":[12,20,34,37,52,59,98,105,113,138,182],"data":[13],"from":[14],"heterogeneous":[15],"populations.":[16],"Maximum":[17],"likelihood":[18],"estimation":[19],"parameters":[22],"is":[23,46,149,205],"typically":[24],"carried":[25],"out":[26],"via":[27],"Expectation-Maximization":[29],"(EM)":[30],"algorithm.":[31],"The":[32,199],"complexity":[33],"implementation":[36],"algorithm":[39,101,115],"depends":[40],"on":[41,168],"parametric":[43],"distribution":[44],"that":[45,74,174],"adopted":[47],"as":[48,176],"component":[50],"densities":[51],"model.":[55],"In":[56,90],"case":[58],"skew":[61,64,193,196],"normal":[62],"t-distributions,":[65],"example,":[67],"E-step":[69],"would":[70],"involve":[71],"complicated":[72],"expressions":[73],"are":[75],"computationally":[76],"expensive":[77],"to":[78,110,127,135,153,159],"evaluate.":[79],"This":[80],"can":[81,123],"become":[82],"quite":[83],"time-consuming":[84],"large":[86],"and/or":[87],"high-dimensional":[88],"datasets.":[89,210],"this":[91],"paper,":[92],"we":[93,166],"develop":[94],"a":[95,169],"multithreaded":[96],"version":[97],"EM":[100],"fitting":[104],"finite":[106],"models.":[108,198],"Due":[109],"structure":[112],"these":[117],"models,":[118],"E-":[120],"M-steps":[122],"be":[124,128],"easily":[125],"reformulated":[126],"executed":[129],"in":[130,143],"parallel":[131],"across":[132],"multiple":[133],"threads":[134],"take":[136],"advantage":[137],"processing":[140],"power":[141],"available":[142],"modern-day":[144],"multicore":[145],"machines.":[146],"Our":[147],"approach":[148,204],"simple":[150],"easy":[152],"implement,":[154],"requiring":[155],"only":[156],"small":[157],"changes":[158],"standard":[160],"code.":[161],"To":[162],"illustrate":[163],"approach,":[165],"focus":[167],"fairly":[170],"general":[171],"model":[173],"includes":[175],"special":[177],"or":[178],"limiting":[179],"cases":[180],"some":[181],"most":[184],"commonly":[185],"including":[189],"normal,":[191,194],"t-,":[192],"t-mixture":[197],"performance":[200],"gain":[201],"with":[202],"our":[203],"illustrated":[206],"using":[207],"two":[208],"real":[209]},"counts_by_year":[{"year":2024,"cited_by_count":3},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2015,"cited_by_count":1}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}