{"id":"https://openalex.org/W2118073449","doi":"https://doi.org/10.1109/cvpr.2008.4587467","title":"Robust estimation of gaussian mixtures from noisy input data","display_name":"Robust estimation of gaussian mixtures from noisy input data","publication_year":2008,"publication_date":"2008-06-01","ids":{"openalex":"https://openalex.org/W2118073449","doi":"https://doi.org/10.1109/cvpr.2008.4587467","mag":"2118073449"},"language":"en","primary_location":{"id":"doi:10.1109/cvpr.2008.4587467","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2008.4587467","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 IEEE Conference on Computer Vision and Pattern Recognition","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/A5102945798","display_name":"Shaobo Hou","orcid":"https://orcid.org/0000-0002-6181-5452"},"institutions":[{"id":"https://openalex.org/I28407311","display_name":"University of Manchester","ror":"https://ror.org/027m9bs27","country_code":"GB","type":"education","lineage":["https://openalex.org/I28407311"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Shaobo Hou","raw_affiliation_strings":["School of Computer Science, University of Manchester, Institute of Science and Technology, UK","Sch. of Comput. Sci., Manchester Univ., Manchester"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, University of Manchester, Institute of Science and Technology, UK","institution_ids":["https://openalex.org/I28407311"]},{"raw_affiliation_string":"Sch. of Comput. Sci., Manchester Univ., Manchester","institution_ids":["https://openalex.org/I28407311"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5070379662","display_name":"Aphrodite Galata","orcid":"https://orcid.org/0000-0002-9229-7811"},"institutions":[{"id":"https://openalex.org/I28407311","display_name":"University of Manchester","ror":"https://ror.org/027m9bs27","country_code":"GB","type":"education","lineage":["https://openalex.org/I28407311"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Aphrodite Galata","raw_affiliation_strings":["School of Computer Science, University of Manchester, Institute of Science and Technology, UK","Sch. of Comput. Sci., Manchester Univ., Manchester"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, University of Manchester, Institute of Science and Technology, UK","institution_ids":["https://openalex.org/I28407311"]},{"raw_affiliation_string":"Sch. of Comput. Sci., Manchester Univ., Manchester","institution_ids":["https://openalex.org/I28407311"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.5878,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.79283023,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"17","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":0.9991000294685364,"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":0.9991000294685364,"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/T11871","display_name":"Advanced Statistical Methods and Models","score":0.982699990272522,"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"}},{"id":"https://openalex.org/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9746999740600586,"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/cluster-analysis","display_name":"Cluster analysis","score":0.7352249026298523},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.6088781952857971},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6028810739517212},{"id":"https://openalex.org/keywords/covariance","display_name":"Covariance","score":0.5829253792762756},{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.5694229006767273},{"id":"https://openalex.org/keywords/bayes-theorem","display_name":"Bayes' theorem","score":0.536084771156311},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4848843514919281},{"id":"https://openalex.org/keywords/synthetic-data","display_name":"Synthetic data","score":0.4658055901527405},{"id":"https://openalex.org/keywords/covariance-matrix","display_name":"Covariance matrix","score":0.4651772677898407},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.44285863637924194},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.4374338984489441},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4234654903411865},{"id":"https://openalex.org/keywords/estimation-of-covariance-matrices","display_name":"Estimation of covariance matrices","score":0.4110192060470581},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.383344829082489},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.37562528252601624},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3284249007701874},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1465519368648529}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7352249026298523},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.6088781952857971},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6028810739517212},{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.5829253792762756},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.5694229006767273},{"id":"https://openalex.org/C207201462","wikidata":"https://www.wikidata.org/wiki/Q182505","display_name":"Bayes' theorem","level":3,"score":0.536084771156311},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4848843514919281},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.4658055901527405},{"id":"https://openalex.org/C185142706","wikidata":"https://www.wikidata.org/wiki/Q1134404","display_name":"Covariance matrix","level":2,"score":0.4651772677898407},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.44285863637924194},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.4374338984489441},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4234654903411865},{"id":"https://openalex.org/C180877172","wikidata":"https://www.wikidata.org/wiki/Q5401390","display_name":"Estimation of covariance matrices","level":3,"score":0.4110192060470581},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.383344829082489},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.37562528252601624},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3284249007701874},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1465519368648529},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/cvpr.2008.4587467","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2008.4587467","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 IEEE Conference on Computer Vision and Pattern Recognition","raw_type":"proceedings-article"},{"id":"pmh:oai:pure.atira.dk:openaire_cris_publications/2d5ea906-8357-4e1a-b1c4-a16318a0d911","is_oa":false,"landing_page_url":"https://research.manchester.ac.uk/en/publications/2d5ea906-8357-4e1a-b1c4-a16318a0d911","pdf_url":null,"source":{"id":"https://openalex.org/S4306400662","display_name":"Research Explorer (The University of Manchester)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I28407311","host_organization_name":"University of Manchester","host_organization_lineage":["https://openalex.org/I28407311"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Hou, S & Galata, A 2008, Robust estimation of gaussian mixtures from noisy input data. in 26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR|IEEE Conf. Comput. Vis. Pattern Recogn., CVPR. IEEE, 26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR, Anchorage, AK, 1/07/08. https://doi.org/10.1109/CVPR.2008.4587467","raw_type":"info:eu-repo/semantics/publishedVersion"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.159.2415","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.159.2415","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cs.man.ac.uk/~agalata/publications/HGcvpr2008.pdf","raw_type":"text"},{"id":"pmh:oai:pure.atira.dk:publications/2d5ea906-8357-4e1a-b1c4-a16318a0d911","is_oa":false,"landing_page_url":"https://www.research.manchester.ac.uk/portal/en/publications/robust-estimation-of-gaussian-mixtures-from-noisy-input-data(2d5ea906-8357-4e1a-b1c4-a16318a0d911).html","pdf_url":null,"source":{"id":"https://openalex.org/S4306400662","display_name":"Research Explorer (The University of Manchester)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I28407311","host_organization_name":"University of Manchester","host_organization_lineage":["https://openalex.org/I28407311"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Hou, S & Galata, A 2008, Robust estimation of gaussian mixtures from noisy input data. in 26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR|IEEE Conf. Comput. Vis. Pattern Recogn., CVPR. IEEE, 26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR, Anchorage, AK, 1/07/08. https://doi.org/10.1109/CVPR.2008.4587467","raw_type":"info:eu-repo/semantics/publishedVersion"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W3161171","https://openalex.org/W20363889","https://openalex.org/W1663973292","https://openalex.org/W1995636725","https://openalex.org/W2024532878","https://openalex.org/W2031390061","https://openalex.org/W2049633694","https://openalex.org/W2099413512","https://openalex.org/W2102943360","https://openalex.org/W2125319195","https://openalex.org/W2130103520","https://openalex.org/W2164723873","https://openalex.org/W2168175751","https://openalex.org/W2171653751","https://openalex.org/W2399173023","https://openalex.org/W2594639291","https://openalex.org/W4235169531","https://openalex.org/W4285719527","https://openalex.org/W6675694798","https://openalex.org/W6679064668","https://openalex.org/W6679388247"],"related_works":["https://openalex.org/W2921280830","https://openalex.org/W2887132723","https://openalex.org/W2572601863","https://openalex.org/W1670628120","https://openalex.org/W2756533552","https://openalex.org/W4286579657","https://openalex.org/W1976318097","https://openalex.org/W1974588588","https://openalex.org/W1583261817","https://openalex.org/W2547004481"],"abstract_inverted_index":{"We":[0],"propose":[1],"a":[2],"variational":[3,94],"bayes":[4],"approach":[5],"to":[6,46,92],"the":[7,26,37,40,49,52,57,75,84,88],"problem":[8],"of":[9,12,39,51,59,87],"robust":[10],"estimation":[11],"gaussian":[13,53],"mixtures":[14],"from":[15],"noisy":[16],"input":[17],"data.":[18],"The":[19],"proposed":[20],"algorithm":[21],"explicitly":[22],"takes":[23],"into":[24,74],"account":[25],"uncertainty":[27,72],"associated":[28],"with":[29],"each":[30],"data":[31,65,90],"point,":[32],"makes":[33],"no":[34],"assumptions":[35],"about":[36],"structure":[38],"covariance":[41],"matrices":[42],"and":[43,62],"is":[44],"able":[45],"automatically":[47],"determine":[48],"number":[50],"mixture":[54],"components.":[55],"Through":[56],"use":[58],"both":[60],"synthetic":[61],"real":[63],"world":[64],"examples,":[66],"we":[67,78],"show":[68],"that":[69],"by":[70],"incorporating":[71],"information":[73],"clustering":[76,96],"algorithm,":[77],"get":[79],"better":[80],"results":[81],"at":[82],"recovering":[83],"true":[85],"distribution":[86],"training":[89],"compared":[91],"other":[93],"bayesian":[95],"algorithms.":[97]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2016,"cited_by_count":1},{"year":2014,"cited_by_count":2},{"year":2013,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
