{"id":"https://openalex.org/W1908089688","doi":"https://doi.org/10.1109/cvpr.2015.7298821","title":"Subspace clustering by Mixture of Gaussian Regression","display_name":"Subspace clustering by Mixture of Gaussian Regression","publication_year":2015,"publication_date":"2015-06-01","ids":{"openalex":"https://openalex.org/W1908089688","doi":"https://doi.org/10.1109/cvpr.2015.7298821","mag":"1908089688"},"language":"en","primary_location":{"id":"doi:10.1109/cvpr.2015.7298821","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2015.7298821","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)","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/A5100705576","display_name":"Baohua Li","orcid":"https://orcid.org/0000-0002-4876-2659"},"institutions":[{"id":"https://openalex.org/I27357992","display_name":"Dalian University of Technology","ror":"https://ror.org/023hj5876","country_code":"CN","type":"education","lineage":["https://openalex.org/I27357992"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Baohua Li","raw_affiliation_strings":["Dalian University of Technology"],"affiliations":[{"raw_affiliation_string":"Dalian University of Technology","institution_ids":["https://openalex.org/I27357992"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100727132","display_name":"Ying Zhang","orcid":"https://orcid.org/0000-0002-2917-2338"},"institutions":[{"id":"https://openalex.org/I27357992","display_name":"Dalian University of Technology","ror":"https://ror.org/023hj5876","country_code":"CN","type":"education","lineage":["https://openalex.org/I27357992"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ying Zhang","raw_affiliation_strings":["Dalian University of Technology"],"affiliations":[{"raw_affiliation_string":"Dalian University of Technology","institution_ids":["https://openalex.org/I27357992"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016399094","display_name":"Zhouchen Lin","orcid":"https://orcid.org/0000-0003-1493-7569"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhouchen Lin","raw_affiliation_strings":["Cooperative Medianet Innovation Center, Shanghai, China","Key Laboratory of Machine Perception (MOE). School of EECS. Peking University"],"affiliations":[{"raw_affiliation_string":"Cooperative Medianet Innovation Center, Shanghai, China","institution_ids":[]},{"raw_affiliation_string":"Key Laboratory of Machine Perception (MOE). School of EECS. Peking University","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102749145","display_name":"Huchuan Lu","orcid":null},"institutions":[{"id":"https://openalex.org/I27357992","display_name":"Dalian University of Technology","ror":"https://ror.org/023hj5876","country_code":"CN","type":"education","lineage":["https://openalex.org/I27357992"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huchuan Lu","raw_affiliation_strings":["Dalian University of Technology"],"affiliations":[{"raw_affiliation_string":"Dalian University of Technology","institution_ids":["https://openalex.org/I27357992"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100705576"],"corresponding_institution_ids":["https://openalex.org/I27357992"],"apc_list":null,"apc_paid":null,"fwci":7.1077,"has_fulltext":false,"cited_by_count":53,"citation_normalized_percentile":{"value":0.97978454,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":"24","issue":null,"first_page":"2094","last_page":"2102"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10057","display_name":"Face and Expression Recognition","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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":0.9919000267982483,"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"}},{"id":"https://openalex.org/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.984000027179718,"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":0.7339555025100708},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.6063759922981262},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5557650923728943},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5502963066101074},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5122038722038269},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5046600103378296},{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.5013868808746338},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4585871398448944},{"id":"https://openalex.org/keywords/gaussian-noise","display_name":"Gaussian noise","score":0.44478660821914673},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.43554067611694336},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.42708820104599},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2662479281425476},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.2268080711364746}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7339555025100708},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.6063759922981262},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5557650923728943},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5502963066101074},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5122038722038269},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5046600103378296},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.5013868808746338},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4585871398448944},{"id":"https://openalex.org/C4199805","wikidata":"https://www.wikidata.org/wiki/Q2725903","display_name":"Gaussian noise","level":2,"score":0.44478660821914673},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.43554067611694336},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.42708820104599},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2662479281425476},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.2268080711364746},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cvpr.2015.7298821","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2015.7298821","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W62203920","https://openalex.org/W1533128638","https://openalex.org/W1578099820","https://openalex.org/W1591385104","https://openalex.org/W1600471557","https://openalex.org/W1950520880","https://openalex.org/W1979293691","https://openalex.org/W1993962865","https://openalex.org/W1994197834","https://openalex.org/W1997201895","https://openalex.org/W2002260165","https://openalex.org/W2003361735","https://openalex.org/W2052311585","https://openalex.org/W2053742104","https://openalex.org/W2101290767","https://openalex.org/W2112796928","https://openalex.org/W2118154608","https://openalex.org/W2118858274","https://openalex.org/W2121148353","https://openalex.org/W2121947440","https://openalex.org/W2125742596","https://openalex.org/W2126761607","https://openalex.org/W2129812935","https://openalex.org/W2132914434","https://openalex.org/W2134199473","https://openalex.org/W2151155403","https://openalex.org/W2152714163","https://openalex.org/W2160915541","https://openalex.org/W2164931791","https://openalex.org/W2165874743","https://openalex.org/W2177347332","https://openalex.org/W2504108613","https://openalex.org/W2994340921","https://openalex.org/W6602535662","https://openalex.org/W6635552349","https://openalex.org/W6635884019","https://openalex.org/W6640861363","https://openalex.org/W6684578312"],"related_works":["https://openalex.org/W2151402979","https://openalex.org/W1964408341","https://openalex.org/W31220157","https://openalex.org/W2312753042","https://openalex.org/W4289356671","https://openalex.org/W2389155397","https://openalex.org/W2165884543","https://openalex.org/W3186837933","https://openalex.org/W2368989808","https://openalex.org/W1969346022"],"abstract_inverted_index":{"Subspace":[0],"clustering":[1,22,78,135],"is":[2,32,50,56,111],"a":[3,7,17,61,83,97,105],"problem":[4],"of":[5,44,71,85,101,117],"finding":[6],"multi-subspace":[8],"representation":[9],"that":[10,36,128],"best":[11],"fits":[12],"sample":[13],"points":[14],"drawn":[15],"from":[16],"high-dimensional":[18],"space.":[19],"The":[20,88],"existing":[21],"models":[23],"generally":[24],"adopt":[25],"different":[26],"norms":[27],"to":[28,34,58,64,95],"describe":[29],"noise,":[30],"which":[31],"equivalent":[33],"assuming":[35],"the":[37,107,115],"data":[38,118],"are":[39],"corrupted":[40],"by":[41,79],"specific":[42],"types":[43],"noise.":[45,66],"In":[46],"practice,":[47],"however,":[48],"noise":[49,81,102],"much":[51,98],"more":[52],"complex.":[53],"So":[54],"it":[55],"inappropriate":[57],"simply":[59],"use":[60],"certain":[62],"norm":[63],"model":[65,96],"Therefore,":[67],"we":[68],"propose":[69],"Mixture":[70,84],"Gaussian":[72],"Regression":[73,90,130],"(MoG":[74],"Regression)":[75],"for":[76],"subspace":[77,134],"modeling":[80],"as":[82],"Gaussians":[86],"(MoG).":[87],"MoG":[89,129],"provides":[91],"an":[92],"effective":[93],"way":[94],"broader":[99],"range":[100],"distributions.":[103],"As":[104],"result,":[106],"obtained":[108],"affinity":[109],"matrix":[110],"better":[112],"at":[113],"characterizing":[114],"structure":[116],"in":[119],"real":[120],"applications.":[121],"Experimental":[122],"results":[123],"on":[124],"multiple":[125],"datasets":[126],"demonstrate":[127],"significantly":[131],"outperforms":[132],"state-of-the-art":[133],"methods.":[136]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":3},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":5},{"year":2018,"cited_by_count":19},{"year":2017,"cited_by_count":10},{"year":2016,"cited_by_count":8},{"year":2015,"cited_by_count":1}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}
