{"id":"https://openalex.org/W2536221661","doi":"https://doi.org/10.1109/acpr.2011.6166658","title":"Discriminative model selection for Gaussian mixture models for classification","display_name":"Discriminative model selection for Gaussian mixture models for classification","publication_year":2011,"publication_date":"2011-11-01","ids":{"openalex":"https://openalex.org/W2536221661","doi":"https://doi.org/10.1109/acpr.2011.6166658","mag":"2536221661"},"language":"en","primary_location":{"id":"doi:10.1109/acpr.2011.6166658","is_oa":false,"landing_page_url":"https://doi.org/10.1109/acpr.2011.6166658","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The First Asian Conference on 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/A5100370790","display_name":"Xiaohua Liu","orcid":"https://orcid.org/0000-0003-0384-5431"},"institutions":[{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]},{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xiao-Hua Liu","raw_affiliation_strings":["National Laboratory of Pattern Recognition (NLPR), Institute of Automation, Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"National Laboratory of Pattern Recognition (NLPR), Institute of Automation, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210112150","https://openalex.org/I19820366"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100714202","display_name":"Cheng\u2010Lin Liu","orcid":"https://orcid.org/0000-0002-6743-4175"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Cheng-Lin Liu","raw_affiliation_strings":["National Laboratory of Pattern Recognition (NLPR), Institute of Automation, Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"National Laboratory of Pattern Recognition (NLPR), Institute of Automation, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210112150","https://openalex.org/I19820366"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5100370790"],"corresponding_institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210112150"],"apc_list":null,"apc_paid":null,"fwci":0.8552,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.81973294,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":"28","issue":null,"first_page":"62","last_page":"66"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9997000098228455,"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":0.9997000098228455,"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":0.9422000050544739,"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":0.9247000217437744,"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/discriminative-model","display_name":"Discriminative model","score":0.9137261509895325},{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.8865447044372559},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7334938049316406},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7096678018569946},{"id":"https://openalex.org/keywords/model-selection","display_name":"Model selection","score":0.6510058641433716},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6086024641990662},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.605256199836731},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.559869647026062},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.44527676701545715},{"id":"https://openalex.org/keywords/mixture-theory","display_name":"Mixture theory","score":0.42337003350257874},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3740030825138092}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.9137261509895325},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.8865447044372559},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7334938049316406},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7096678018569946},{"id":"https://openalex.org/C93959086","wikidata":"https://www.wikidata.org/wiki/Q6888345","display_name":"Model selection","level":2,"score":0.6510058641433716},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6086024641990662},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.605256199836731},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.559869647026062},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.44527676701545715},{"id":"https://openalex.org/C2779736610","wikidata":"https://www.wikidata.org/wiki/Q6884140","display_name":"Mixture theory","level":3,"score":0.42337003350257874},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3740030825138092},{"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/acpr.2011.6166658","is_oa":false,"landing_page_url":"https://doi.org/10.1109/acpr.2011.6166658","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The First Asian Conference on Pattern Recognition","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7699999809265137,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W46365459","https://openalex.org/W1551188508","https://openalex.org/W1579271636","https://openalex.org/W2015245929","https://openalex.org/W2048850031","https://openalex.org/W2049633694","https://openalex.org/W2097579995","https://openalex.org/W2102098892","https://openalex.org/W2106554350","https://openalex.org/W2109820980","https://openalex.org/W2114759290","https://openalex.org/W2127928018","https://openalex.org/W2128716185","https://openalex.org/W2132549764","https://openalex.org/W2142635246","https://openalex.org/W2146610201","https://openalex.org/W2168175751","https://openalex.org/W2168993425","https://openalex.org/W2170973289","https://openalex.org/W2488678869","https://openalex.org/W3149745985","https://openalex.org/W6674528451"],"related_works":["https://openalex.org/W1578916557","https://openalex.org/W2095350775","https://openalex.org/W2146591867","https://openalex.org/W1975321310","https://openalex.org/W1853799209","https://openalex.org/W792241301","https://openalex.org/W2025931908","https://openalex.org/W1998035802","https://openalex.org/W1579833936","https://openalex.org/W2536221661"],"abstract_inverted_index":{"The":[0,38,86],"Gaussian":[1],"mixture":[2,23],"model":[3,39,54,87,103],"(GMM)":[4],"has":[5],"been":[6],"widely":[7],"used":[8],"in":[9,69,90],"pattern":[10],"recognition":[11],"problems":[12],"for":[13],"clustering":[14],"and":[15],"probability":[16],"density":[17],"estimation.":[18],"Given":[19],"the":[20,27,35,59,66,72,82,113,118],"number":[21],"of":[22,29,61,74,117],"components":[24],"(model":[25],"order),":[26],"parameters":[28],"GMM":[30],"can":[31],"be":[32],"estimated":[33],"by":[34],"EM":[36],"algorithm.":[37],"order":[40],"selection,":[41],"however,":[42],"remains":[43],"an":[44],"open":[45],"problem.":[46],"For":[47],"classification":[48,84,115],"purpose,":[49],"we":[50],"propose":[51],"a":[52],"discriminative":[53,92],"selection":[55],"method":[56],"to":[57,80,96],"optimize":[58],"orders":[60,73,88],"all":[62,75],"classes.":[63],"Based":[64],"on":[65,108],"GMMs":[67],"initialized":[68],"some":[70,109],"way,":[71],"classes":[76],"are":[77,94],"adjusted":[78],"heuristically":[79],"improve":[81],"cross-validated":[83],"accuracy.":[85],"selected":[89],"this":[91],"way":[93],"expected":[95],"give":[97],"higher":[98],"generalized":[99],"accuracy":[100],"than":[101],"classwise":[102],"selection.":[104],"Our":[105],"experimental":[106],"results":[107],"UCI":[110],"datasets":[111],"demonstrate":[112],"superior":[114],"performance":[116],"proposed":[119],"method.":[120]},"counts_by_year":[{"year":2014,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}