{"id":"https://openalex.org/W4381747237","doi":"https://doi.org/10.1145/3589845.3589854","title":"Multi-view Subspace Clustering with Complex Noise Modeling","display_name":"Multi-view Subspace Clustering with Complex Noise Modeling","publication_year":2023,"publication_date":"2023-01-06","ids":{"openalex":"https://openalex.org/W4381747237","doi":"https://doi.org/10.1145/3589845.3589854"},"language":"en","primary_location":{"id":"doi:10.1145/3589845.3589854","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3589845.3589854","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 9th International Conference on Computing and Data Engineering","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/A5070930354","display_name":"Xiangyu Lu","orcid":"https://orcid.org/0000-0002-9282-540X"},"institutions":[{"id":"https://openalex.org/I204512498","display_name":"University of Macau","ror":"https://ror.org/01r4q9n85","country_code":"MO","type":"education","lineage":["https://openalex.org/I204512498"]}],"countries":["MO"],"is_corresponding":true,"raw_author_name":"Xiangyu Lu","raw_affiliation_strings":["Dept. of Computer and Information Science, University of Macau, China"],"affiliations":[{"raw_affiliation_string":"Dept. of Computer and Information Science, University of Macau, China","institution_ids":["https://openalex.org/I204512498"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074728748","display_name":"Lingzhi Zhu","orcid":"https://orcid.org/0000-0002-3363-5067"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lingzhi Zhu","raw_affiliation_strings":["School of Electronic and Optical Engineering, Nanjing University of Science and Technology, China"],"affiliations":[{"raw_affiliation_string":"School of Electronic and Optical Engineering, Nanjing University of Science and Technology, China","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5069402421","display_name":"Yuyang Sun","orcid":"https://orcid.org/0000-0001-7703-4127"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuyang Sun","raw_affiliation_strings":["School of Electronic and Optical Engineering, Nanjing University of Science and Technology, China"],"affiliations":[{"raw_affiliation_string":"School of Electronic and Optical Engineering, Nanjing University of Science and Technology, China","institution_ids":["https://openalex.org/I36399199"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5070930354"],"corresponding_institution_ids":["https://openalex.org/I204512498"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.05909352,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"48","last_page":"57"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9954000115394592,"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":0.9954000115394592,"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":0.9789000153541565,"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/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9782000184059143,"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":0.8327183723449707},{"id":"https://openalex.org/keywords/cure-data-clustering-algorithm","display_name":"CURE data clustering algorithm","score":0.6950593590736389},{"id":"https://openalex.org/keywords/correlation-clustering","display_name":"Correlation clustering","score":0.6877328157424927},{"id":"https://openalex.org/keywords/data-stream-clustering","display_name":"Data stream clustering","score":0.6725293397903442},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6401504874229431},{"id":"https://openalex.org/keywords/canopy-clustering-algorithm","display_name":"Canopy clustering algorithm","score":0.6023069620132446},{"id":"https://openalex.org/keywords/clustering-high-dimensional-data","display_name":"Clustering high-dimensional data","score":0.5534934997558594},{"id":"https://openalex.org/keywords/fuzzy-clustering","display_name":"Fuzzy clustering","score":0.4902949631214142},{"id":"https://openalex.org/keywords/affinity-propagation","display_name":"Affinity propagation","score":0.48809611797332764},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4567093253135681},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.45066747069358826},{"id":"https://openalex.org/keywords/spectral-clustering","display_name":"Spectral clustering","score":0.44463402032852173},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.43651413917541504},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4358307123184204}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.8327183723449707},{"id":"https://openalex.org/C33704608","wikidata":"https://www.wikidata.org/wiki/Q5014717","display_name":"CURE data clustering algorithm","level":4,"score":0.6950593590736389},{"id":"https://openalex.org/C94641424","wikidata":"https://www.wikidata.org/wiki/Q5172845","display_name":"Correlation clustering","level":3,"score":0.6877328157424927},{"id":"https://openalex.org/C193143536","wikidata":"https://www.wikidata.org/wiki/Q5227360","display_name":"Data stream clustering","level":5,"score":0.6725293397903442},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6401504874229431},{"id":"https://openalex.org/C104047586","wikidata":"https://www.wikidata.org/wiki/Q5033439","display_name":"Canopy clustering algorithm","level":4,"score":0.6023069620132446},{"id":"https://openalex.org/C184509293","wikidata":"https://www.wikidata.org/wiki/Q5136711","display_name":"Clustering high-dimensional data","level":3,"score":0.5534934997558594},{"id":"https://openalex.org/C17212007","wikidata":"https://www.wikidata.org/wiki/Q5511111","display_name":"Fuzzy clustering","level":3,"score":0.4902949631214142},{"id":"https://openalex.org/C109659709","wikidata":"https://www.wikidata.org/wiki/Q3407504","display_name":"Affinity propagation","level":5,"score":0.48809611797332764},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4567093253135681},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.45066747069358826},{"id":"https://openalex.org/C105611402","wikidata":"https://www.wikidata.org/wiki/Q2976589","display_name":"Spectral clustering","level":3,"score":0.44463402032852173},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.43651413917541504},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4358307123184204},{"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:10.1145/3589845.3589854","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3589845.3589854","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 9th International Conference on Computing and Data Engineering","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W1981458038","https://openalex.org/W1987805576","https://openalex.org/W1988626117","https://openalex.org/W1993962865","https://openalex.org/W2007518603","https://openalex.org/W2016285269","https://openalex.org/W2030507150","https://openalex.org/W2034630192","https://openalex.org/W2045551057","https://openalex.org/W2050267927","https://openalex.org/W2109857912","https://openalex.org/W2125464731","https://openalex.org/W2135320312","https://openalex.org/W2141985649","https://openalex.org/W2156483112","https://openalex.org/W2195250169","https://openalex.org/W2279323413","https://openalex.org/W2748391982","https://openalex.org/W2808465901","https://openalex.org/W2910342528","https://openalex.org/W2944309706","https://openalex.org/W2981337591","https://openalex.org/W3024343454","https://openalex.org/W3121417152","https://openalex.org/W3128355817","https://openalex.org/W3130527475","https://openalex.org/W3176694003","https://openalex.org/W4249938415","https://openalex.org/W4250657332","https://openalex.org/W4292363360","https://openalex.org/W4365800035"],"related_works":["https://openalex.org/W2362911195","https://openalex.org/W2794209582","https://openalex.org/W2352610727","https://openalex.org/W2245611357","https://openalex.org/W2358586643","https://openalex.org/W4301002638","https://openalex.org/W2065347048","https://openalex.org/W2897883632","https://openalex.org/W2371010743","https://openalex.org/W2330550450"],"abstract_inverted_index":{"Multi-view":[0],"data":[1,13,49],"clustering":[2,17,23,28,46,56,63,104,165],"often":[3],"aims":[4],"to":[5,14,20,32,101,148],"utilize":[6],"various":[7],"representations":[8],"or":[9],"views":[10,85],"of":[11,37,83,86],"original":[12,108],"improve":[15,149],"the":[16,21,34,73,91,103,107,111,116,122],"performance":[18],"compared":[19],"single-view":[22],"approach.":[24],"Most":[25],"multi-view":[26,48,52,66],"subspace":[27,55,67,75,164],"methods":[29,166],"are":[30,96],"proposed":[31,159],"construct":[33],"affinity":[35,80],"matrix":[36,81],"each":[38],"view":[39],"individually":[40],"and":[41,61,93,139],"then":[42],"implement":[43],"with":[44],"spectral":[45],"for":[47,146],"clustering.":[50,68],"The":[51,152],"low-rank":[53,92],"sparse":[54],"(MLRSSC)":[57],"is":[58],"an":[59,79],"effective":[60],"popular":[62],"algorithm":[64,160],"among":[65],"This":[69],"method":[70,100],"can":[71],"explore":[72],"joint":[74],"representation":[76],"through":[77],"creating":[78],"integrated":[82],"all":[84],"input":[87],"data.":[88],"In":[89],"addition,":[90],"sparsity":[94],"constraints":[95],"introduced":[97],"into":[98],"this":[99,158],"enhance":[102],"results.":[105],"However,":[106],"MLRSSC":[109,147],"uses":[110],"mean":[112],"square":[113],"error":[114],"as":[115],"fidelity":[117],"term":[118],"while":[119],"not":[120],"consider":[121],"complex":[123,133],"noise":[124,134,144],"pollution":[125],"in":[126],"real":[127],"situations.":[128],"Therefore,":[129],"we":[130],"introduce":[131],"a":[132],"modeling":[135],"approach,":[136],"i.e.,":[137],"independent":[138],"piecewise":[140],"identically":[141],"distributed":[142],"(IPID)":[143],"model,":[145],"its":[150],"performance.":[151],"related":[153],"experimental":[154],"results":[155],"confirm":[156],"that":[157],"surpasses":[161],"many":[162],"state-of-the-art":[163],"on":[167],"several":[168],"real-world":[169],"datasets.":[170]},"counts_by_year":[],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
