{"id":"https://openalex.org/W1985222096","doi":"https://doi.org/10.1109/tnnls.2014.2334711","title":"Kernel Reconstruction ICA for Sparse Representation","display_name":"Kernel Reconstruction ICA for Sparse Representation","publication_year":2014,"publication_date":"2014-07-23","ids":{"openalex":"https://openalex.org/W1985222096","doi":"https://doi.org/10.1109/tnnls.2014.2334711","mag":"1985222096","pmid":"https://pubmed.ncbi.nlm.nih.gov/25069125"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2014.2334711","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2014.2334711","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/A5033428547","display_name":"Yanhui Xiao","orcid":null},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanhui Xiao","raw_affiliation_strings":["Beijing Key Laboratory of Advanced Information Science and Network Technology, Beijing, China","Institute of Information Science, Beijing Jiaotong University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Key Laboratory of Advanced Information Science and Network Technology, Beijing, China","institution_ids":[]},{"raw_affiliation_string":"Institute of Information Science, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101867605","display_name":"Zhenfeng Zhu","orcid":"https://orcid.org/0000-0001-7315-3276"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenfeng Zhu","raw_affiliation_strings":["Beijing Key Laboratory of Advanced Information Science and Network Technology, Beijing, China","Institute of Information Science, Beijing Jiaotong University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Key Laboratory of Advanced Information Science and Network Technology, Beijing, China","institution_ids":[]},{"raw_affiliation_string":"Institute of Information Science, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110382448","display_name":"Yao Zhao","orcid":"https://orcid.org/0009-0006-1092-3302"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yao Zhao","raw_affiliation_strings":["Institute of Information Science, Beijing Jiaotong University","State Key Laboratory of Rail Traffic Control and Safety, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Information Science, Beijing Jiaotong University","institution_ids":["https://openalex.org/I21193070"]},{"raw_affiliation_string":"State Key Laboratory of Rail Traffic Control and Safety, Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087043856","display_name":"Yunchao Wei","orcid":"https://orcid.org/0000-0002-2812-8781"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yunchao Wei","raw_affiliation_strings":["Beijing Key Laboratory of Advanced Information Science and Network Technology, Beijing, China","Institute of Information Science, Beijing Jiaotong University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Key Laboratory of Advanced Information Science and Network Technology, Beijing, China","institution_ids":[]},{"raw_affiliation_string":"Institute of Information Science, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5006854141","display_name":"Shikui Wei","orcid":"https://orcid.org/0000-0003-3803-9763"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shikui Wei","raw_affiliation_strings":["Beijing Key Laboratory of Advanced Information Science and Network Technology, Beijing, China","Institute of Information Science, Beijing Jiaotong University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Key Laboratory of Advanced Information Science and Network Technology, Beijing, China","institution_ids":[]},{"raw_affiliation_string":"Institute of Information Science, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I21193070"],"apc_list":null,"apc_paid":null,"fwci":1.7379,"has_fulltext":false,"cited_by_count":20,"citation_normalized_percentile":{"value":0.84296798,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"26","issue":"6","first_page":"1222","last_page":"1232"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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":0.9991999864578247,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.995199978351593,"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/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.681014895439148},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.6671167612075806},{"id":"https://openalex.org/keywords/sparse-approximation","display_name":"Sparse approximation","score":0.6168303489685059},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.5691598653793335},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.54060959815979},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.536274254322052},{"id":"https://openalex.org/keywords/separable-space","display_name":"Separable space","score":0.5342639684677124},{"id":"https://openalex.org/keywords/basis","display_name":"Basis (linear algebra)","score":0.5166166424751282},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.511520504951477},{"id":"https://openalex.org/keywords/constraint","display_name":"Constraint (computer-aided design)","score":0.4989919662475586},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4931918978691101},{"id":"https://openalex.org/keywords/kernel-method","display_name":"Kernel method","score":0.4418541193008423},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.3970828354358673},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.3124943971633911}],"concepts":[{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.681014895439148},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.6671167612075806},{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.6168303489685059},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.5691598653793335},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.54060959815979},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.536274254322052},{"id":"https://openalex.org/C70710897","wikidata":"https://www.wikidata.org/wiki/Q680081","display_name":"Separable space","level":2,"score":0.5342639684677124},{"id":"https://openalex.org/C12426560","wikidata":"https://www.wikidata.org/wiki/Q189569","display_name":"Basis (linear algebra)","level":2,"score":0.5166166424751282},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.511520504951477},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.4989919662475586},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4931918978691101},{"id":"https://openalex.org/C122280245","wikidata":"https://www.wikidata.org/wiki/Q620622","display_name":"Kernel method","level":3,"score":0.4418541193008423},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3970828354358673},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.3124943971633911},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","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},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"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/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","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},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/tnnls.2014.2334711","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2014.2334711","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:25069125","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/25069125","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},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.771.685","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.771.685","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://arxiv.org/pdf/1304.2490.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.5299999713897705},{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.4699999988079071}],"awards":[{"id":"https://openalex.org/G1376897105","display_name":"\u89c6\u9891\u5e7f\u544a\u76d1\u64ad\u4e2d\u7684\u8de8\u5a92\u4f53\u5206\u6790\u7406\u8bba\u4e0e\u6280\u672f\u7814\u7a76","funder_award_id":"61172129","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1936986885","display_name":null,"funder_award_id":"IRT201206","funder_id":"https://openalex.org/F4320338204","funder_display_name":"Program for Changjiang Scholars and Innovative Research Team in University"},{"id":"https://openalex.org/G4434262924","display_name":null,"funder_award_id":"2012JBZ012","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G6548964774","display_name":null,"funder_award_id":"13-0661","funder_id":"https://openalex.org/F4320334924","funder_display_name":"Program for New Century Excellent Talents in University"},{"id":"https://openalex.org/G6649631323","display_name":null,"funder_award_id":"61202241","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7833407414","display_name":null,"funder_award_id":"61025013","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8017731688","display_name":null,"funder_award_id":"2012CB316400","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G8436593353","display_name":null,"funder_award_id":"61210006","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/F4320334924","display_name":"Program for New Century Excellent Talents in University","ror":"https://ror.org/01mv9t934"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null},{"id":"https://openalex.org/F4320338204","display_name":"Program for Changjiang Scholars and Innovative Research Team in University","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":54,"referenced_works":["https://openalex.org/W104211377","https://openalex.org/W104847522","https://openalex.org/W1510073064","https://openalex.org/W1548802052","https://openalex.org/W1576445103","https://openalex.org/W1588424744","https://openalex.org/W1591116419","https://openalex.org/W1808256548","https://openalex.org/W1902027874","https://openalex.org/W1979558950","https://openalex.org/W1988914719","https://openalex.org/W2027805700","https://openalex.org/W2050834445","https://openalex.org/W2054502547","https://openalex.org/W2084716923","https://openalex.org/W2097018403","https://openalex.org/W2098207052","https://openalex.org/W2104819583","https://openalex.org/W2110798204","https://openalex.org/W2112274848","https://openalex.org/W2114570910","https://openalex.org/W2118858186","https://openalex.org/W2119667497","https://openalex.org/W2120480077","https://openalex.org/W2129812935","https://openalex.org/W2136922672","https://openalex.org/W2145889472","https://openalex.org/W2146672645","https://openalex.org/W2151103935","https://openalex.org/W2160547390","https://openalex.org/W2160840682","https://openalex.org/W2162931300","https://openalex.org/W2166049352","https://openalex.org/W2169574652","https://openalex.org/W2253807446","https://openalex.org/W2296319761","https://openalex.org/W2296616510","https://openalex.org/W2536599074","https://openalex.org/W4205778870","https://openalex.org/W4232730838","https://openalex.org/W4235713725","https://openalex.org/W4244288018","https://openalex.org/W4250955649","https://openalex.org/W4285719527","https://openalex.org/W6604310120","https://openalex.org/W6634343353","https://openalex.org/W6638482740","https://openalex.org/W6674642818","https://openalex.org/W6676481782","https://openalex.org/W6676759488","https://openalex.org/W6677233944","https://openalex.org/W6677919164","https://openalex.org/W6678242812","https://openalex.org/W6683965311"],"related_works":["https://openalex.org/W1584385814","https://openalex.org/W2089892314","https://openalex.org/W1603091392","https://openalex.org/W4386075310","https://openalex.org/W2095626363","https://openalex.org/W2169565408","https://openalex.org/W2127229869","https://openalex.org/W3123056048","https://openalex.org/W2129978300","https://openalex.org/W2150638158"],"abstract_inverted_index":{"Independent":[0],"component":[1],"analysis":[2],"with":[3,17],"soft":[4],"reconstruction":[5],"cost":[6],"(RICA)":[7],"has":[8],"been":[9],"recently":[10],"proposed":[11,184],"to":[12,100,114,163],"linearly":[13,85],"learn":[14],"sparse":[15,103],"representation":[16,104,151,156],"an":[18,59,176],"overcomplete":[19],"basis,":[20],"and":[21,62,153,167],"this":[22],"technique":[23],"exhibits":[24],"promising":[25],"performance":[26],"even":[27],"on":[28,136,193],"unwhitened":[29],"data.":[30],"However,":[31],"linear":[32],"RICA":[33,56,97],"may":[34],"not":[35,64],"be":[36],"effective":[37,188],"for":[38],"the":[39,70,73,111,126,130,137,140,172,183],"majority":[40],"of":[41,72,139,143],"real-world":[42],"data":[43,47,53,81,127],"because":[44],"nonlinearly":[45,79,101],"separable":[46,80,86],"structure":[48,82],"pervasively":[49],"exists":[50],"in":[51,88,105,175],"original":[52],"space.":[54,107],"Meanwhile,":[55],"is":[57,160,186],"essentially":[58,161],"unsupervised":[60,112],"method":[61],"does":[63],"employ":[65],"class":[66,132],"information.":[67],"Motivated":[68],"by":[69,118],"success":[71],"kernel":[74,96],"trick":[75],"that":[76,125,182],"maps":[77],"a":[78,84,89,95,115,120],"into":[83],"case":[87],"high-dimensional":[90],"feature":[91,106],"space,":[92],"we":[93,109],"propose":[94],"(kRICA)":[98],"model":[99],"capture":[102],"Furthermore,":[108],"extend":[110],"kRICA":[113],"supervised":[116],"one":[117],"introducing":[119],"class-driven":[121],"discrimination":[122,147],"constraint,":[123],"such":[124],"samples":[128],"from":[129],"same":[131,173],"are":[133],"well":[134],"represented":[135],"basis":[138,144],"corresponding":[141],"subset":[142],"vectors.":[145],"This":[146],"constraint":[148],"minimizes":[149],"inhomogeneous":[150],"energy":[152,157],"maximizes":[154],"homogeneous":[155],"simultaneously,":[158],"which":[159],"equivalent":[162],"maximizing":[164],"between-class":[165],"scatter":[166,170],"minimizing":[168],"within-class":[169],"at":[171],"time":[174],"implicit":[177],"manner.":[178],"Experimental":[179],"results":[180],"demonstrate":[181],"algorithm":[185],"more":[187],"than":[189],"other":[190],"state-of-the-art":[191],"methods":[192],"several":[194],"datasets.":[195]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":4},{"year":2013,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
