{"id":"https://openalex.org/W2811398175","doi":"https://doi.org/10.1109/tcyb.2018.2846404","title":"Regularized Gaussian Mixture Model for High-Dimensional Clustering","display_name":"Regularized Gaussian Mixture Model for High-Dimensional Clustering","publication_year":2018,"publication_date":"2018-06-27","ids":{"openalex":"https://openalex.org/W2811398175","doi":"https://doi.org/10.1109/tcyb.2018.2846404","mag":"2811398175","pmid":"https://pubmed.ncbi.nlm.nih.gov/29994696"},"language":"en","primary_location":{"id":"doi:10.1109/tcyb.2018.2846404","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcyb.2018.2846404","pdf_url":null,"source":{"id":"https://openalex.org/S4210191041","display_name":"IEEE Transactions on Cybernetics","issn_l":"2168-2267","issn":["2168-2267","2168-2275"],"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 Transactions on Cybernetics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5115565883","display_name":"Yang Zhao","orcid":"https://orcid.org/0000-0003-1571-5394"},"institutions":[{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"education","lineage":["https://openalex.org/I168719708"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Yang Zhao","raw_affiliation_strings":["Centre for Systems Informatics Engineering, City University of Hong Kong, Hong Kong"],"raw_orcid":"https://orcid.org/0000-0003-1571-5394","affiliations":[{"raw_affiliation_string":"Centre for Systems Informatics Engineering, City University of Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I168719708"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064533871","display_name":"Abhishek K. Shrivastava","orcid":"https://orcid.org/0000-0002-6779-4832"},"institutions":[{"id":"https://openalex.org/I1305444813","display_name":"Capital One (United States)","ror":"https://ror.org/00svp7168","country_code":"US","type":"company","lineage":["https://openalex.org/I1305444813"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Abhishek K. Shrivastava","raw_affiliation_strings":["Data Science, Capital One, Plano, TX, USA"],"raw_orcid":"https://orcid.org/0000-0002-6779-4832","affiliations":[{"raw_affiliation_string":"Data Science, Capital One, Plano, TX, USA","institution_ids":["https://openalex.org/I1305444813"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5002878668","display_name":"Kwok\u2010Leung Tsui","orcid":"https://orcid.org/0000-0002-0558-2279"},"institutions":[{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"education","lineage":["https://openalex.org/I168719708"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Kwok Leung Tsui","raw_affiliation_strings":["Department of Systems Engineering and Engineering Management, City University of Hong Kong, Hong Kong"],"raw_orcid":"https://orcid.org/0000-0002-0558-2279","affiliations":[{"raw_affiliation_string":"Department of Systems Engineering and Engineering Management, City University of Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I168719708"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.2759,"has_fulltext":false,"cited_by_count":44,"citation_normalized_percentile":{"value":0.93670555,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"49","issue":"10","first_page":"3677","last_page":"3688"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9995999932289124,"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":0.9995999932289124,"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/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9819999933242798,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9613000154495239,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.8106181621551514},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.7221848368644714},{"id":"https://openalex.org/keywords/covariance","display_name":"Covariance","score":0.5782518982887268},{"id":"https://openalex.org/keywords/expectation\u2013maximization-algorithm","display_name":"Expectation\u2013maximization algorithm","score":0.5781737565994263},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5464751124382019},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5204886794090271},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.515956699848175},{"id":"https://openalex.org/keywords/linear-subspace","display_name":"Linear subspace","score":0.45344430208206177},{"id":"https://openalex.org/keywords/clustering-high-dimensional-data","display_name":"Clustering high-dimensional data","score":0.4510105550289154},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.45098787546157837},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.4506330192089081},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4497418999671936},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.4457041323184967},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.4321766495704651},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3760487735271454},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3746204376220703},{"id":"https://openalex.org/keywords/maximum-likelihood","display_name":"Maximum likelihood","score":0.14016050100326538},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.10317537188529968}],"concepts":[{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.8106181621551514},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7221848368644714},{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.5782518982887268},{"id":"https://openalex.org/C182081679","wikidata":"https://www.wikidata.org/wiki/Q1275153","display_name":"Expectation\u2013maximization algorithm","level":3,"score":0.5781737565994263},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5464751124382019},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5204886794090271},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.515956699848175},{"id":"https://openalex.org/C12362212","wikidata":"https://www.wikidata.org/wiki/Q728435","display_name":"Linear subspace","level":2,"score":0.45344430208206177},{"id":"https://openalex.org/C184509293","wikidata":"https://www.wikidata.org/wiki/Q5136711","display_name":"Clustering high-dimensional data","level":3,"score":0.4510105550289154},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.45098787546157837},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.4506330192089081},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4497418999671936},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.4457041323184967},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.4321766495704651},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3760487735271454},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3746204376220703},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.14016050100326538},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.10317537188529968},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tcyb.2018.2846404","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcyb.2018.2846404","pdf_url":null,"source":{"id":"https://openalex.org/S4210191041","display_name":"IEEE Transactions on Cybernetics","issn_l":"2168-2267","issn":["2168-2267","2168-2275"],"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 Transactions on Cybernetics","raw_type":"journal-article"},{"id":"pmid:29994696","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/29994696","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on cybernetics","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3051707253","display_name":"\u6545\u969c\u9884\u6d4b\u548c\u7cfb\u7edf\u5065\u5eb7\u7ba1\u7406\u7684\u8d1d\u53f6\u65af\u63a8\u65ad","funder_award_id":"11471275","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":63,"referenced_works":["https://openalex.org/W1506806321","https://openalex.org/W1594453127","https://openalex.org/W1614659291","https://openalex.org/W1662191912","https://openalex.org/W1975120776","https://openalex.org/W1975517862","https://openalex.org/W1975842137","https://openalex.org/W1977556410","https://openalex.org/W1979775288","https://openalex.org/W1981706894","https://openalex.org/W1992419399","https://openalex.org/W2009086942","https://openalex.org/W2011058684","https://openalex.org/W2011832962","https://openalex.org/W2019303707","https://openalex.org/W2021137021","https://openalex.org/W2024318675","https://openalex.org/W2040263621","https://openalex.org/W2041823554","https://openalex.org/W2049633694","https://openalex.org/W2052793367","https://openalex.org/W2053259742","https://openalex.org/W2053742104","https://openalex.org/W2059606882","https://openalex.org/W2060542593","https://openalex.org/W2071128523","https://openalex.org/W2072248825","https://openalex.org/W2078957532","https://openalex.org/W2081746825","https://openalex.org/W2089322632","https://openalex.org/W2097714737","https://openalex.org/W2098318489","https://openalex.org/W2099322651","https://openalex.org/W2103537693","https://openalex.org/W2107790343","https://openalex.org/W2120211304","https://openalex.org/W2130136434","https://openalex.org/W2131102540","https://openalex.org/W2132555912","https://openalex.org/W2132763547","https://openalex.org/W2134507164","https://openalex.org/W2140369911","https://openalex.org/W2142584058","https://openalex.org/W2151128232","https://openalex.org/W2152012752","https://openalex.org/W2153922613","https://openalex.org/W2157142743","https://openalex.org/W2157267184","https://openalex.org/W2161419360","https://openalex.org/W2167388003","https://openalex.org/W2168980979","https://openalex.org/W2169694221","https://openalex.org/W2268212270","https://openalex.org/W2304523937","https://openalex.org/W2313022313","https://openalex.org/W2543290761","https://openalex.org/W3103385725","https://openalex.org/W3103917751","https://openalex.org/W4232396098","https://openalex.org/W6635771633","https://openalex.org/W6637034065","https://openalex.org/W6674952872","https://openalex.org/W6682227116"],"related_works":["https://openalex.org/W3100286349","https://openalex.org/W2896134808","https://openalex.org/W4289378085","https://openalex.org/W4294291164","https://openalex.org/W3172436493","https://openalex.org/W1887135636","https://openalex.org/W4287164812","https://openalex.org/W2386063599","https://openalex.org/W1975884855","https://openalex.org/W3213150849"],"abstract_inverted_index":{"Finding":[0],"low-dimensional":[1,91],"representation":[2],"of":[3,63,93,102,122,149,166],"high-dimensional":[4,84],"data":[5,17,158,175],"sets":[6,18],"is":[7,153],"an":[8],"important":[9],"task":[10],"in":[11,23,35,47,83,99,112,170],"various":[12],"applications.":[13],"The":[14,86,106,134,147],"fact":[15],"that":[16,37],"often":[19],"contain":[20],"clusters":[21],"embedded":[22],"different":[24],"subspaces":[25],"poses":[26],"barrier":[27],"to":[28,130],"this":[29,48],"task.":[30],"Driven":[31],"by":[32],"the":[33,61,94,113,119,126,132,150,163,167],"need":[34],"methods":[36],"enable":[38],"clustering":[39],"and":[40,70],"finding":[41],"each":[42],"cluster's":[43],"intrinsic":[44],"subspace":[45],"simultaneously,":[46],"paper,":[49],"we":[50],"propose":[51],"a":[52,123,138],"regularized":[53],"Gaussian":[54],"mixture":[55],"model":[56],"(GMM)":[57],"for":[58,78,117],"clustering.":[59],"Despite":[60],"advantages":[62],"GMM,":[64,124],"such":[65],"as":[66],"its":[67],"probabilistic":[68],"interpretation":[69],"robustness":[71],"against":[72],"observation":[73],"noise,":[74],"traditional":[75],"maximum-likelihood":[76],"estimation":[77,101],"GMMs":[79],"shows":[80],"disappointing":[81],"performance":[82,148],"setting.":[85],"proposed":[87,151,168],"regularization":[88,107],"method":[89,152,169],"finds":[90],"representations":[92],"component":[95],"covariance":[96],"matrices,":[97],"resulting":[98],"better":[100],"local":[103],"feature":[104],"correlations.":[105],"problem":[108],"can":[109,143],"be":[110,144],"incorporated":[111],"expectation":[114],"maximization":[115,140],"algorithm":[116],"maximizing":[118],"likelihood":[120],"function":[121],"with":[125],"M":[127,135],"-step":[128,136],"modified":[129],"incorporate":[131],"regularization.":[133],"involves":[137],"determinant":[139],"problem,":[141],"which":[142],"solved":[145],"efficiently.":[146],"demonstrated":[154],"using":[155,172],"several":[156],"simulated":[157],"sets.":[159,176],"We":[160],"also":[161],"illustrate":[162],"potential":[164],"value":[165],"applications":[171],"four":[173],"real":[174]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":13},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":5}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}