{"id":"https://openalex.org/W2608831636","doi":"https://doi.org/10.1109/icpr.2016.7900195","title":"Robust unsupervised feature selection by nonnegative sparse subspace learning","display_name":"Robust unsupervised feature selection by nonnegative sparse subspace learning","publication_year":2016,"publication_date":"2016-12-01","ids":{"openalex":"https://openalex.org/W2608831636","doi":"https://doi.org/10.1109/icpr.2016.7900195","mag":"2608831636"},"language":"en","primary_location":{"id":"doi:10.1109/icpr.2016.7900195","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2016.7900195","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 23rd International Conference on Pattern Recognition (ICPR)","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/A5100401082","display_name":"Wei Zheng","orcid":"https://orcid.org/0000-0002-0666-521X"},"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":true,"raw_author_name":"Wei Zheng","raw_affiliation_strings":["School of Computer Science and Engineering Nanjing University of Science and Technology, Nanjing, P.R. China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering Nanjing University of Science and Technology, Nanjing, P.R. China","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101969406","display_name":"Hui Yan","orcid":"https://orcid.org/0000-0001-8332-9255"},"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":"Hui Yan","raw_affiliation_strings":["School of Computer Science and Engineering Nanjing University of Science and Technology, Nanjing, P.R. China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering Nanjing University of Science and Technology, Nanjing, P.R. China","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100726984","display_name":"Jian Yang","orcid":"https://orcid.org/0000-0003-4800-832X"},"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":"Jian Yang","raw_affiliation_strings":["School of Computer Science and Engineering Nanjing University of Science and Technology, Nanjing, P.R. China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering Nanjing University of Science and Technology, Nanjing, P.R. China","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5063288559","display_name":"Jingyu Yang","orcid":"https://orcid.org/0000-0002-7521-7920"},"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":"Jingyu Yang","raw_affiliation_strings":["School of Computer Science and Engineering Nanjing University of Science and Technology, Nanjing, P.R. China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering Nanjing University of Science and Technology, Nanjing, P.R. China","institution_ids":["https://openalex.org/I36399199"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100401082"],"corresponding_institution_ids":["https://openalex.org/I36399199"],"apc_list":null,"apc_paid":null,"fwci":0.167,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.6167117,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"48","issue":null,"first_page":"3615","last_page":"3620"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9995999932289124,"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":0.9995999932289124,"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":0.9980000257492065,"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/T12676","display_name":"Machine Learning and ELM","score":0.9937000274658203,"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/computer-science","display_name":"Computer science","score":0.6071382761001587},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.5725201964378357},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.5700094699859619},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5671136379241943},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.5646848678588867},{"id":"https://openalex.org/keywords/non-negative-matrix-factorization","display_name":"Non-negative matrix factorization","score":0.5024631023406982},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4921538233757019},{"id":"https://openalex.org/keywords/multiplicative-function","display_name":"Multiplicative function","score":0.4828636944293976},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.41895899176597595},{"id":"https://openalex.org/keywords/matrix-decomposition","display_name":"Matrix decomposition","score":0.3698297142982483},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3504452705383301},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3470161557197571},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2750966548919678}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6071382761001587},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.5725201964378357},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.5700094699859619},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5671136379241943},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.5646848678588867},{"id":"https://openalex.org/C152671427","wikidata":"https://www.wikidata.org/wiki/Q10843505","display_name":"Non-negative matrix factorization","level":4,"score":0.5024631023406982},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4921538233757019},{"id":"https://openalex.org/C42747912","wikidata":"https://www.wikidata.org/wiki/Q1048447","display_name":"Multiplicative function","level":2,"score":0.4828636944293976},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.41895899176597595},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.3698297142982483},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3504452705383301},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3470161557197571},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2750966548919678},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.0},{"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/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","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},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icpr.2016.7900195","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2016.7900195","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 23rd International Conference on Pattern Recognition (ICPR)","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":35,"referenced_works":["https://openalex.org/W7470303","https://openalex.org/W120692785","https://openalex.org/W140777655","https://openalex.org/W141062567","https://openalex.org/W628583573","https://openalex.org/W1520757484","https://openalex.org/W1607408214","https://openalex.org/W1736339626","https://openalex.org/W1922017469","https://openalex.org/W1979999753","https://openalex.org/W2009501510","https://openalex.org/W2015648984","https://openalex.org/W2076363162","https://openalex.org/W2121007818","https://openalex.org/W2128873747","https://openalex.org/W2129812935","https://openalex.org/W2135029798","https://openalex.org/W2149620660","https://openalex.org/W2157690157","https://openalex.org/W2168901348","https://openalex.org/W2171837816","https://openalex.org/W2314735922","https://openalex.org/W2478708596","https://openalex.org/W2799061466","https://openalex.org/W4230946174","https://openalex.org/W6604905834","https://openalex.org/W6605792473","https://openalex.org/W6631064309","https://openalex.org/W6636281135","https://openalex.org/W6677853180","https://openalex.org/W6680012447","https://openalex.org/W6681822384","https://openalex.org/W6683523906","https://openalex.org/W6929385289","https://openalex.org/W7014191107"],"related_works":["https://openalex.org/W1995723671","https://openalex.org/W2164647769","https://openalex.org/W4390394189","https://openalex.org/W2149305241","https://openalex.org/W2037504162","https://openalex.org/W2539013788","https://openalex.org/W2792706544","https://openalex.org/W1568451138","https://openalex.org/W2902260311","https://openalex.org/W2156699640"],"abstract_inverted_index":{"Sparse":[0],"subspace":[1,35],"learning":[2],"has":[3],"been":[4],"demonstrated":[5],"to":[6,79,86,101,112,142],"be":[7],"effective":[8],"in":[9,77],"data":[10,74],"mining":[11],"and":[12,54,103,116,120,149,161],"machine":[13],"learning.":[14,36],"In":[15],"this":[16,114],"paper,":[17],"we":[18,84,135,150],"cast":[19],"the":[20,31,39,42,48,55,61,67,73,81,121,145],"unsupervised":[21],"feature":[22,44,146],"selection":[23],"scenario":[24],"as":[25],"a":[26,137],"matrix":[27,46],"factorization":[28],"problem":[29,89],"from":[30,130],"view":[32],"of":[33,72,123,168],"sparse":[34,104],"By":[37],"minimizing":[38],"reconstruction":[40],"residual,":[41],"learned":[43],"weight":[45,147],"with":[47,160],"l":[49,91],"<inf":[50,92],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[51,93],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">2,1</inf>":[52],"-norm":[53,95],"non-negative":[56,132],"constraints":[57],"not":[58],"only":[59],"removes":[60],"irrelevant":[62],"features,":[63],"but":[64],"also":[65],"captures":[66],"underlying":[68],"low":[69],"dimensional":[70],"structure":[71],"points.":[75],"Meanwhile":[76],"order":[78],"enhance":[80],"model's":[82],"robustness,":[83],"attempt":[85],"solve":[87,144],"our":[88,169],"by":[90],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">1</inf>":[94],"error":[96],"function":[97,119],"which":[98],"is":[99,110,126],"resistant":[100],"outliers":[102],"noise.":[105],"An":[106],"efficient":[107],"iterative":[108],"algorithm":[109],"introduced":[111],"optimize":[113],"non-convex":[115],"non-smooth":[117],"objective":[118],"proof":[122],"its":[124,152],"convergence":[125],"given.":[127],"Particularly,":[128],"differ":[129],"conventional":[131],"updating":[133],"rules,":[134],"design":[136],"novel":[138],"multiplicative":[139],"update":[140],"rule":[141],"iteratively":[143],"matrix,":[148],"validate":[151],"non-negativity.":[153],"Comparative":[154],"experiments":[155],"on":[156],"various":[157],"original":[158],"datasets":[159],"without":[162],"malicious":[163],"pollution":[164],"demonstrate":[165],"performance":[166],"superiority":[167],"model.":[170]},"counts_by_year":[{"year":2018,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}