{"id":"https://openalex.org/W4319993347","doi":"https://doi.org/10.1109/tnnls.2023.3238103","title":"Fast Sparse Discriminative K-Means for Unsupervised Feature Selection","display_name":"Fast Sparse Discriminative K-Means for Unsupervised Feature Selection","publication_year":2023,"publication_date":"2023-01-25","ids":{"openalex":"https://openalex.org/W4319993347","doi":"https://doi.org/10.1109/tnnls.2023.3238103","pmid":"https://pubmed.ncbi.nlm.nih.gov/37022041"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2023.3238103","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2023.3238103","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Neural Networks and Learning Systems","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/A5003222421","display_name":"Feiping Nie","orcid":"https://orcid.org/0000-0002-0871-6519"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]},{"id":"https://openalex.org/I890469752","display_name":"Ministry of Industry and Information Technology","ror":"https://ror.org/0385nmy68","country_code":"CN","type":"government","lineage":["https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Feiping Nie","raw_affiliation_strings":["School of Artificial Intelligence, OPtics and ElectroNics (iOPEN) and the Key Laboratory of Intelligent Interaction and Applications, Ministry of Industry and Information Technology, Northwestern Polytechnical University, Xi&#x2019;an, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, OPtics and ElectroNics (iOPEN) and the Key Laboratory of Intelligent Interaction and Applications, Ministry of Industry and Information Technology, Northwestern Polytechnical University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I890469752","https://openalex.org/I17145004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069982028","display_name":"Zhenyu Ma","orcid":"https://orcid.org/0000-0002-3745-3471"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenyu Ma","raw_affiliation_strings":["School of Astronautics, Northwestern Polytechnical University, Xi&#x2019;an, China"],"affiliations":[{"raw_affiliation_string":"School of Astronautics, Northwestern Polytechnical University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100432452","display_name":"Jingyu Wang","orcid":"https://orcid.org/0000-0001-7017-1938"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingyu Wang","raw_affiliation_strings":["School of Astronautics and the School of Artificial Intelligence, OPtics and ElectroNics (iOPEN), Northwestern Polytechnical University, Xi&#x2019;an, China"],"affiliations":[{"raw_affiliation_string":"School of Astronautics and the School of Artificial Intelligence, OPtics and ElectroNics (iOPEN), Northwestern Polytechnical University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5106943753","display_name":"Xuelong Li","orcid":"https://orcid.org/0000-0003-2924-946X"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]},{"id":"https://openalex.org/I890469752","display_name":"Ministry of Industry and Information Technology","ror":"https://ror.org/0385nmy68","country_code":"CN","type":"government","lineage":["https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuelong Li","raw_affiliation_strings":["School of Artificial Intelligence, OPtics and ElectroNics (iOPEN) and the Key Laboratory of Intelligent Interaction and Applications, Ministry of Industry and Information Technology, Northwestern Polytechnical University, Xi&#x2019;an, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, OPtics and ElectroNics (iOPEN) and the Key Laboratory of Intelligent Interaction and Applications, Ministry of Industry and Information Technology, Northwestern Polytechnical University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I890469752","https://openalex.org/I17145004"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5003222421"],"corresponding_institution_ids":["https://openalex.org/I17145004","https://openalex.org/I890469752"],"apc_list":null,"apc_paid":null,"fwci":4.6941,"has_fulltext":false,"cited_by_count":39,"citation_normalized_percentile":{"value":0.9615284,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":"35","issue":"7","first_page":"9943","last_page":"9957"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9941999912261963,"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":0.9941999912261963,"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9889000058174133,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T13731","display_name":"Advanced Computing and Algorithms","score":0.9648000001907349,"subfield":{"id":"https://openalex.org/subfields/3322","display_name":"Urban Studies"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.7064600586891174},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.6111451387405396},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.5669860243797302},{"id":"https://openalex.org/keywords/notation","display_name":"Notation","score":0.5010340213775635},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.4910144805908203},{"id":"https://openalex.org/keywords/norm","display_name":"Norm (philosophy)","score":0.4451432228088379},{"id":"https://openalex.org/keywords/constraint","display_name":"Constraint (computer-aided design)","score":0.43810850381851196},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.43684375286102295},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4106754958629608},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.402179092168808},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3270763158798218},{"id":"https://openalex.org/keywords/arithmetic","display_name":"Arithmetic","score":0.09992715716362}],"concepts":[{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.7064600586891174},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.6111451387405396},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.5669860243797302},{"id":"https://openalex.org/C45357846","wikidata":"https://www.wikidata.org/wiki/Q2001982","display_name":"Notation","level":2,"score":0.5010340213775635},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.4910144805908203},{"id":"https://openalex.org/C191795146","wikidata":"https://www.wikidata.org/wiki/Q3878446","display_name":"Norm (philosophy)","level":2,"score":0.4451432228088379},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.43810850381851196},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.43684375286102295},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4106754958629608},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.402179092168808},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3270763158798218},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.09992715716362},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","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},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2023.3238103","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2023.3238103","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:37022041","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/37022041","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 neural networks and learning systems","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.75,"id":"https://metadata.un.org/sdg/10"}],"awards":[{"id":"https://openalex.org/G1530037185","display_name":null,"funder_award_id":"61976179","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4820425477","display_name":null,"funder_award_id":"61871470","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":0,"referenced_works":[],"related_works":["https://openalex.org/W2965546495","https://openalex.org/W4389116644","https://openalex.org/W2153315159","https://openalex.org/W3103844505","https://openalex.org/W259157601","https://openalex.org/W4205463238","https://openalex.org/W2761785940","https://openalex.org/W2110523656","https://openalex.org/W1482209366","https://openalex.org/W2521627374"],"abstract_inverted_index":{"Embedded":[0],"feature":[1,19,50,74,148],"selection":[2,20,51,75,104,131,149],"approach":[3],"guides":[4],"subsequent":[5],"projection":[6],"matrix":[7,16,26,81,102,105,132],"(selection":[8],"matrix)":[9],"learning":[10],"through":[11],"the":[12,23,66,73,78,114,119,127,138,153,162,173,182,192],"acquisition":[13],"of":[14,130,175,196],"pseudolabel":[15,25,80,101],"to":[17,38,87,112,125,160,180],"conduct":[18],"tasks.":[21],"Yet":[22],"continuous":[24],"learned":[27],"from":[28,36,91,152],"relaxed":[29],"problem":[30],"based":[31],"on":[32,187],"spectral":[33],"analysis":[34],"deviates":[35],"reality":[37],"some":[39],"extent.":[40],"To":[41],"cope":[42],"with":[43,82,133,172],"this":[44,95],"issue,":[45],"we":[46],"design":[47],"an":[48],"efficient":[49],"framework":[52,150],"inspired":[53],"by":[54],"classical":[55],"least-squares":[56],"regression":[57,164],"(LSR)":[58],"and":[59,103,156,194],"discriminative":[60,69],"K-means":[61,70],"(DisK-means),":[62],"which":[63,108,177],"is":[64,85,106,109,123,169,178],"called":[65],"fast":[67],"sparse":[68,163],"(FSDK)":[71],"for":[72],"method.":[76],"First,":[77],"weighted":[79],"discrete":[83],"trait":[84],"introduced":[86,124],"avoid":[88],"trivial":[89],"solution":[90],"unsupervised":[92],"LSR.":[93],"On":[94],"condition,":[96],"any":[97],"constraint":[98],"imposed":[99],"into":[100],"dispensable,":[107],"significantly":[110],"beneficial":[111],"simplify":[113],"combinational":[115],"optimization":[116],"problem.":[117,165],"Second,":[118],"l<sub>2,p</sub>":[120,157],"-norm":[121,158],"regularizer":[122,159],"satisfy":[126],"row":[128],"sparsity":[129],"flexible":[134],"p":[135],".":[136],"Consequently,":[137],"proposed":[139],"FSDK":[140],"model":[141,168],"can":[142],"be":[143],"treated":[144],"as":[145],"a":[146],"novel":[147],"integrated":[151],"DisK-means":[154],"algorithm":[155],"optimize":[161],"Moreover,":[166],"our":[167],"linearly":[170],"correlated":[171],"number":[174],"samples,":[176],"speedy":[179],"handle":[181],"large-scale":[183],"data.":[184],"Comprehensive":[185],"tests":[186],"various":[188],"data":[189],"terminally":[190],"illuminate":[191],"effectiveness":[193],"efficiency":[195],"FSDK.":[197]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":20},{"year":2024,"cited_by_count":15},{"year":2023,"cited_by_count":3}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
