{"id":"https://openalex.org/W4365420209","doi":"https://doi.org/10.1109/tkde.2023.3266595","title":"C<sup>2</sup>IMUFS: Complementary and Consensus Learning-Based Incomplete Multi-View Unsupervised Feature Selection","display_name":"C<sup>2</sup>IMUFS: Complementary and Consensus Learning-Based Incomplete Multi-View Unsupervised Feature Selection","publication_year":2023,"publication_date":"2023-04-12","ids":{"openalex":"https://openalex.org/W4365420209","doi":"https://doi.org/10.1109/tkde.2023.3266595"},"language":"en","primary_location":{"id":"doi:10.1109/tkde.2023.3266595","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2023.3266595","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Knowledge and Data Engineering","raw_type":"journal-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/A5071469942","display_name":"Yanyong Huang","orcid":"https://orcid.org/0000-0001-9322-2777"},"institutions":[{"id":"https://openalex.org/I204831749","display_name":"Southwestern University of Finance and Economics","ror":"https://ror.org/04ewct822","country_code":"CN","type":"education","lineage":["https://openalex.org/I204831749"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanyong Huang","raw_affiliation_strings":["School of Statistics, Southwestern University of Finance and Economics, Chengdu, China"],"raw_orcid":"https://orcid.org/0000-0001-9322-2777","affiliations":[{"raw_affiliation_string":"School of Statistics, Southwestern University of Finance and Economics, Chengdu, China","institution_ids":["https://openalex.org/I204831749"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025821580","display_name":"Zongxin Shen","orcid":"https://orcid.org/0009-0009-6161-1933"},"institutions":[{"id":"https://openalex.org/I204831749","display_name":"Southwestern University of Finance and Economics","ror":"https://ror.org/04ewct822","country_code":"CN","type":"education","lineage":["https://openalex.org/I204831749"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zongxin Shen","raw_affiliation_strings":["School of Statistics, Southwestern University of Finance and Economics, Chengdu, China"],"raw_orcid":"https://orcid.org/0009-0009-6161-1933","affiliations":[{"raw_affiliation_string":"School of Statistics, Southwestern University of Finance and Economics, Chengdu, China","institution_ids":["https://openalex.org/I204831749"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100744837","display_name":"Yuxin Cai","orcid":"https://orcid.org/0009-0002-8452-4479"},"institutions":[{"id":"https://openalex.org/I204831749","display_name":"Southwestern University of Finance and Economics","ror":"https://ror.org/04ewct822","country_code":"CN","type":"education","lineage":["https://openalex.org/I204831749"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuxin Cai","raw_affiliation_strings":["School of Statistics, Southwestern University of Finance and Economics, Chengdu, China"],"raw_orcid":"https://orcid.org/0009-0002-8452-4479","affiliations":[{"raw_affiliation_string":"School of Statistics, Southwestern University of Finance and Economics, Chengdu, China","institution_ids":["https://openalex.org/I204831749"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013889855","display_name":"Xiuwen Yi","orcid":"https://orcid.org/0000-0003-2703-6794"},"institutions":[{"id":"https://openalex.org/I4210103986","display_name":"Jingdong (China)","ror":"https://ror.org/01dkjkq64","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210103986"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiuwen Yi","raw_affiliation_strings":["JD Intelligent Cities Research and JD Intelligent Cities Business Unit, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-2703-6794","affiliations":[{"raw_affiliation_string":"JD Intelligent Cities Research and JD Intelligent Cities Business Unit, Beijing, China","institution_ids":["https://openalex.org/I4210103986"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101737969","display_name":"Dongjie Wang","orcid":"https://orcid.org/0000-0003-3948-0059"},"institutions":[{"id":"https://openalex.org/I106165777","display_name":"University of Central Florida","ror":"https://ror.org/036nfer12","country_code":"US","type":"education","lineage":["https://openalex.org/I106165777"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dongjie Wang","raw_affiliation_strings":["College of Engineering and Computer Science, University of Central Florida, Orlando, FL, USA"],"raw_orcid":"https://orcid.org/0000-0003-3948-0059","affiliations":[{"raw_affiliation_string":"College of Engineering and Computer Science, University of Central Florida, Orlando, FL, USA","institution_ids":["https://openalex.org/I106165777"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009594218","display_name":"Fengmao Lv","orcid":"https://orcid.org/0000-0003-1640-0992"},"institutions":[{"id":"https://openalex.org/I4800084","display_name":"Southwest Jiaotong University","ror":"https://ror.org/00hn7w693","country_code":"CN","type":"education","lineage":["https://openalex.org/I4800084"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fengmao Lv","raw_affiliation_strings":["School of Computing and Artificial Intelligence, Southwest Jiaotong University, Chengdu, China"],"raw_orcid":"https://orcid.org/0000-0003-1640-0992","affiliations":[{"raw_affiliation_string":"School of Computing and Artificial Intelligence, Southwest Jiaotong University, Chengdu, China","institution_ids":["https://openalex.org/I4800084"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5070559820","display_name":"Tianrui Li","orcid":"https://orcid.org/0000-0001-7780-104X"},"institutions":[{"id":"https://openalex.org/I4800084","display_name":"Southwest Jiaotong University","ror":"https://ror.org/00hn7w693","country_code":"CN","type":"education","lineage":["https://openalex.org/I4800084"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tianrui Li","raw_affiliation_strings":["School of Computing and Artificial Intelligence, Southwest Jiaotong University, Chengdu, China"],"raw_orcid":"https://orcid.org/0000-0001-7780-104X","affiliations":[{"raw_affiliation_string":"School of Computing and Artificial Intelligence, Southwest Jiaotong University, Chengdu, China","institution_ids":["https://openalex.org/I4800084"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":4.6576,"has_fulltext":false,"cited_by_count":45,"citation_normalized_percentile":{"value":0.95636145,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"35","issue":"10","first_page":"10681","last_page":"10694"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9969000220298767,"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"}},"topics":[{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9969000220298767,"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/T10057","display_name":"Face and Expression Recognition","score":0.9876000285148621,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9520000219345093,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/notation","display_name":"Notation","score":0.6614993214607239},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5362936854362488},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.528019368648529},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5036072134971619},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4604327082633972},{"id":"https://openalex.org/keywords/unsupervised-learning","display_name":"Unsupervised learning","score":0.45653873682022095},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.43548649549484253},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4214974045753479},{"id":"https://openalex.org/keywords/data-point","display_name":"Data point","score":0.41492295265197754},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.37831735610961914},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.33925145864486694}],"concepts":[{"id":"https://openalex.org/C45357846","wikidata":"https://www.wikidata.org/wiki/Q2001982","display_name":"Notation","level":2,"score":0.6614993214607239},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5362936854362488},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.528019368648529},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5036072134971619},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4604327082633972},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.45653873682022095},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.43548649549484253},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4214974045753479},{"id":"https://openalex.org/C21080849","wikidata":"https://www.wikidata.org/wiki/Q13611879","display_name":"Data point","level":2,"score":0.41492295265197754},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.37831735610961914},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.33925145864486694},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tkde.2023.3266595","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2023.3266595","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Knowledge and Data Engineering","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.5600000023841858}],"awards":[{"id":"https://openalex.org/G1814726428","display_name":null,"funder_award_id":"62076171","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4115684213","display_name":null,"funder_award_id":"62176221","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"},{"id":"https://openalex.org/F4320329795","display_name":"Southwestern University of Finance and Economics","ror":"https://ror.org/04ewct822"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":46,"referenced_works":["https://openalex.org/W1600471557","https://openalex.org/W1644402181","https://openalex.org/W1655434153","https://openalex.org/W1964305049","https://openalex.org/W1984776140","https://openalex.org/W2004544971","https://openalex.org/W2068320780","https://openalex.org/W2069682406","https://openalex.org/W2084028080","https://openalex.org/W2084376194","https://openalex.org/W2094023061","https://openalex.org/W2152828463","https://openalex.org/W2158933803","https://openalex.org/W2168103112","https://openalex.org/W2168190036","https://openalex.org/W2257217404","https://openalex.org/W2336238079","https://openalex.org/W2527508530","https://openalex.org/W2575552627","https://openalex.org/W2577472518","https://openalex.org/W2595272553","https://openalex.org/W2792234535","https://openalex.org/W2808219330","https://openalex.org/W2833504722","https://openalex.org/W2898233200","https://openalex.org/W2898541610","https://openalex.org/W2899604627","https://openalex.org/W2905779127","https://openalex.org/W2906529026","https://openalex.org/W2930181195","https://openalex.org/W3000308450","https://openalex.org/W3014376566","https://openalex.org/W3021342796","https://openalex.org/W3047358409","https://openalex.org/W3109825681","https://openalex.org/W3117306485","https://openalex.org/W3120689699","https://openalex.org/W3123085760","https://openalex.org/W3164408549","https://openalex.org/W3165208855","https://openalex.org/W3176728172","https://openalex.org/W3205539018","https://openalex.org/W3210633742","https://openalex.org/W4200121584","https://openalex.org/W6681822384","https://openalex.org/W6714133674"],"related_works":["https://openalex.org/W2504004674","https://openalex.org/W1987679298","https://openalex.org/W2963177394","https://openalex.org/W4313359513","https://openalex.org/W2498744856","https://openalex.org/W4390482104","https://openalex.org/W20047544","https://openalex.org/W4390806283","https://openalex.org/W2488605529","https://openalex.org/W2364156185"],"abstract_inverted_index":{"Multi-view":[0],"unsupervised":[1,84],"feature":[2,85,97],"selection":[3,86,98],"(MUFS)":[4],"has":[5],"been":[6],"demonstrated":[7],"as":[8,56],"an":[9,57,100],"effective":[10],"technique":[11],"to":[12,68,89,146,174],"reduce":[13],"the":[14,52,69,91,125,148,176,187],"dimensionality":[15],"of":[16,26,39,111,129,189],"multi-view":[17,31,83],"unlabeled":[18],"data.":[19],"The":[20],"existing":[21,62],"methods":[22],"assume":[23],"that":[24],"all":[25,48],"views":[27,45,165],"are":[28,33,41],"complete.":[29],"However,":[30],"data":[32],"usually":[34],"incomplete,":[35],"i.e.,":[36],"a":[37,77,114,137,158,170],"part":[38],"instances":[40],"presented":[42,145],"on":[43,183],"some":[44],"but":[46],"not":[47],"views.":[49,71],"Besides,":[50],"learning":[51,110],"complete":[53,149],"similarity":[54,131,140,150],"graph,":[55],"important":[58],"promising":[59],"technology":[60],"in":[61,152],"MUFS":[63],"methods,":[64],"cannot":[65],"achieve":[66],"due":[67],"missing":[70],"In":[72],"this":[73],"paper,":[74],"we":[75],"propose":[76],"complementary":[78,138],"and":[79,113,122,166],"consensus":[80,159],"learning-based":[81],"incomplete":[82],"method":[87],"(C$^{2}$IMUFS)":[88],"address":[90],"aforementioned":[92],"issues.":[93],"Concretely,":[94],"C$^{2}$IMUFS":[95,156,190],"integrates":[96],"into":[99,169],"extended":[101],"weighted":[102],"non-negative":[103],"matrix":[104,141,162],"factorization":[105],"model":[106,143],"equipped":[107],"with":[108,192],"adaptive":[109],"view-weights":[112],"sparse$\\ell":[115],"_{2,p}$-norm,":[116],"which":[117],"can":[118],"offer":[119],"better":[120],"adaptability":[121],"flexibility.":[123],"By":[124],"sparse":[126],"linear":[127],"combinations":[128],"multiple":[130],"matrices":[132],"derived":[133],"from":[134],"different":[135,164],"views,":[136],"learning-guided":[139],"reconstruction":[142],"is":[144],"obtain":[147],"graph":[151,172],"each":[153],"view.":[154],"Furthermore,":[155],"learns":[157],"clustering":[160],"indicator":[161],"across":[163],"embeds":[167],"it":[168],"spectral":[171],"term":[173],"preserve":[175],"local":[177],"geometric":[178],"structure.":[179],"Comprehensive":[180],"experimental":[181],"results":[182],"real-world":[184],"datasets":[185],"demonstrate":[186],"effectiveness":[188],"compared":[191],"state-of-the-art":[193],"methods.":[194]},"counts_by_year":[{"year":2026,"cited_by_count":12},{"year":2025,"cited_by_count":17},{"year":2024,"cited_by_count":14},{"year":2023,"cited_by_count":2}],"updated_date":"2026-08-12T21:12:35.861297","created_date":"2025-10-10T00:00:00"}