{"id":"https://openalex.org/W2978474062","doi":"https://doi.org/10.1109/ijcnn.2019.8852061","title":"Latent Space Embedding for Unsupervised Feature Selection via Joint Dictionary Learning","display_name":"Latent Space Embedding for Unsupervised Feature Selection via Joint Dictionary Learning","publication_year":2019,"publication_date":"2019-07-01","ids":{"openalex":"https://openalex.org/W2978474062","doi":"https://doi.org/10.1109/ijcnn.2019.8852061","mag":"2978474062"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2019.8852061","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2019.8852061","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 International Joint Conference on Neural Networks (IJCNN)","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/A5114803191","display_name":"Fan Yang","orcid":"https://orcid.org/0009-0006-2092-7104"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yang Fan","raw_affiliation_strings":["College of Intelligence and Computing, Tianjin University, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"College of Intelligence and Computing, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070031719","display_name":"Jianhua Dai","orcid":"https://orcid.org/0000-0003-1459-0833"},"institutions":[{"id":"https://openalex.org/I173759888","display_name":"Hunan Normal University","ror":"https://ror.org/053w1zy07","country_code":"CN","type":"education","lineage":["https://openalex.org/I173759888"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianhua Dai","raw_affiliation_strings":["College of Information Science and Engineering, Hunan Normal University, Changsha, Hunan, China"],"affiliations":[{"raw_affiliation_string":"College of Information Science and Engineering, Hunan Normal University, Changsha, Hunan, China","institution_ids":["https://openalex.org/I173759888"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5014399261","display_name":"Qilai Zhang","orcid":"https://orcid.org/0009-0008-4174-1418"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qilai Zhang","raw_affiliation_strings":["College of Intelligence and Computing, Tianjin University, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"College of Intelligence and Computing, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5114803191"],"corresponding_institution_ids":["https://openalex.org/I162868743"],"apc_list":null,"apc_paid":null,"fwci":0.1012,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.44461305,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"54","issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9994000196456909,"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":0.9994000196456909,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9937999844551086,"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"}},{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9908999800682068,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.674013614654541},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6728285551071167},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6581242084503174},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.6392552256584167},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.6349059343338013},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6176621913909912},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.5785062909126282},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5715844631195068},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.5559035539627075},{"id":"https://openalex.org/keywords/unsupervised-learning","display_name":"Unsupervised learning","score":0.51435387134552},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.4334900379180908}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.674013614654541},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6728285551071167},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6581242084503174},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.6392552256584167},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.6349059343338013},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6176621913909912},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.5785062909126282},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5715844631195068},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5559035539627075},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.51435387134552},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.4334900379180908},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn.2019.8852061","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2019.8852061","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.5600000023841858}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W18701524","https://openalex.org/W120692785","https://openalex.org/W141062567","https://openalex.org/W628583573","https://openalex.org/W1897044480","https://openalex.org/W1992464666","https://openalex.org/W2009501510","https://openalex.org/W2020804487","https://openalex.org/W2042969131","https://openalex.org/W2076261573","https://openalex.org/W2084028080","https://openalex.org/W2128873747","https://openalex.org/W2149620660","https://openalex.org/W2164278908","https://openalex.org/W2166371785","https://openalex.org/W2171837816","https://openalex.org/W2414043010","https://openalex.org/W2554382158","https://openalex.org/W2564482619","https://openalex.org/W2575552627","https://openalex.org/W2740813652","https://openalex.org/W2765804761","https://openalex.org/W2788685622","https://openalex.org/W2905061379","https://openalex.org/W3022909171","https://openalex.org/W4285719527","https://openalex.org/W4292363360","https://openalex.org/W4320931877","https://openalex.org/W6604905834","https://openalex.org/W6605792473","https://openalex.org/W6619899190","https://openalex.org/W6639690344","https://openalex.org/W6652451885","https://openalex.org/W6681822384","https://openalex.org/W6684213969","https://openalex.org/W6715815293","https://openalex.org/W6731078113","https://openalex.org/W6748746125"],"related_works":["https://openalex.org/W2894871804","https://openalex.org/W2133581097","https://openalex.org/W2546942002","https://openalex.org/W2159220931","https://openalex.org/W2944661354","https://openalex.org/W2147802381","https://openalex.org/W3093564170","https://openalex.org/W2592385986","https://openalex.org/W2299646912","https://openalex.org/W2785535669"],"abstract_inverted_index":{"With":[0],"the":[1,42,47,75,93,117,130,151,169],"prevalence":[2],"of":[3,14,50,57,78,95,133,174],"unlabeled":[4,15],"data,":[5],"unsupervised":[6,20,70],"feature":[7,21,58,71,79,88,109,120],"selection":[8,22,89],"is":[9,148],"vital":[10],"for":[11,69],"comprehensive":[12],"analysis":[13,86],"high-dimensional":[16],"data.":[17],"Most":[18],"existing":[19],"methods":[23,171],"first":[24],"generate":[25],"cluster":[26,38],"labels":[27,137],"by":[28,92,108],"specific":[29],"techniques":[30],"and":[31,81,87,111,122,135,157],"then":[32],"select":[33],"features":[34,44,125,134],"that":[35,56,126,165],"can":[36,127],"preserve":[37],"structure":[39],"well.":[40],"However,":[41],"selected":[43],"only":[45],"reflect":[46],"distribution":[48,77,132],"information":[49],"pseudo":[51,82,112,136],"label":[52,83,113],"space":[53,67,80,106,110,121],"but":[54],"ignore":[55],"space.":[59,114],"Instead,":[60],"we":[61,102],"propose":[62],"a":[63,104],"novel":[64],"method,":[65],"latent":[66,105,123],"embedding":[68],"selection,":[72],"which":[73],"considers":[74],"common":[76,131],"space,":[84,124],"spectral":[85],"simultaneously.":[90],"Inspired":[91],"success":[94],"joint":[96],"dictionary":[97],"learning":[98],"in":[99,172],"cross-modality":[100],"cases,":[101],"introduce":[103],"shared":[107],"By":[115],"utilizing":[116],"mapping":[118],"between":[119],"well":[128],"maintain":[129],"are":[138],"selected.":[139],"The":[140],"\u2113":[141],"<sub":[142],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[143],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">2,1</sub>":[144],"-norm":[145],"minimization":[146],"constraint":[147],"added":[149],"to":[150,154],"objective":[152],"function":[153],"handle":[155],"outliers":[156],"noises.":[158],"Experimental":[159],"results":[160],"on":[161],"benchmark":[162],"datasets":[163],"demonstrate":[164],"our":[166],"algorithm":[167],"outperforms":[168],"compared":[170],"terms":[173],"clustering":[175],"tasks.":[176]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}