{"id":"https://openalex.org/W2296557312","doi":"https://doi.org/10.1109/tnnls.2016.2530403","title":"Optimized Kernel Entropy Components","display_name":"Optimized Kernel Entropy Components","publication_year":2016,"publication_date":"2016-02-25","ids":{"openalex":"https://openalex.org/W2296557312","doi":"https://doi.org/10.1109/tnnls.2016.2530403","mag":"2296557312","pmid":"https://pubmed.ncbi.nlm.nih.gov/26930695"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2016.2530403","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2016.2530403","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":["arxiv","crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1603.02806","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5082220927","display_name":"Emma Izquierdo\u2010Verdiguier","orcid":"https://orcid.org/0000-0003-2179-1262"},"institutions":[{"id":"https://openalex.org/I16097986","display_name":"Universitat de Val\u00e8ncia","ror":"https://ror.org/043nxc105","country_code":"ES","type":"education","lineage":["https://openalex.org/I16097986"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Emma Izquierdo-Verdiguier","raw_affiliation_strings":["Image Processing Laboratory, Universitat de Val\u00e8ncia, Valencia, Spain"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Image Processing Laboratory, Universitat de Val\u00e8ncia, Valencia, Spain","institution_ids":["https://openalex.org/I16097986"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065281659","display_name":"Valero Laparra","orcid":"https://orcid.org/0000-0001-7531-9890"},"institutions":[{"id":"https://openalex.org/I16097986","display_name":"Universitat de Val\u00e8ncia","ror":"https://ror.org/043nxc105","country_code":"ES","type":"education","lineage":["https://openalex.org/I16097986"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Valero Laparra","raw_affiliation_strings":["Image Processing Laboratory, Universitat de Val\u00e8ncia, Valencia, Spain"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Image Processing Laboratory, Universitat de Val\u00e8ncia, Valencia, Spain","institution_ids":["https://openalex.org/I16097986"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013414039","display_name":"Robert Jenssen","orcid":"https://orcid.org/0000-0002-7496-8474"},"institutions":[{"id":"https://openalex.org/I78037679","display_name":"UiT The Arctic University of Norway","ror":"https://ror.org/00wge5k78","country_code":"NO","type":"education","lineage":["https://openalex.org/I78037679"]}],"countries":["NO"],"is_corresponding":false,"raw_author_name":"Robert Jenssen","raw_affiliation_strings":["University of Troms\u00f8, Troms\u00f8, Norway"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Troms\u00f8, Troms\u00f8, Norway","institution_ids":["https://openalex.org/I78037679"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000820727","display_name":"Luis G\u00f3mez\u2010Chova","orcid":"https://orcid.org/0000-0003-3924-1269"},"institutions":[{"id":"https://openalex.org/I16097986","display_name":"Universitat de Val\u00e8ncia","ror":"https://ror.org/043nxc105","country_code":"ES","type":"education","lineage":["https://openalex.org/I16097986"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Luis Gomez-Chova","raw_affiliation_strings":["Image Processing Laboratory, Universitat de Val\u00e8ncia, Valencia, Spain"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Image Processing Laboratory, Universitat de Val\u00e8ncia, Valencia, Spain","institution_ids":["https://openalex.org/I16097986"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5039052506","display_name":"Gustau Camps\u2010Valls","orcid":"https://orcid.org/0000-0003-1683-2138"},"institutions":[{"id":"https://openalex.org/I16097986","display_name":"Universitat de Val\u00e8ncia","ror":"https://ror.org/043nxc105","country_code":"ES","type":"education","lineage":["https://openalex.org/I16097986"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Gustau Camps-Valls","raw_affiliation_strings":["Image Processing Laboratory, Universitat de Val\u00e8ncia, Valencia, Spain"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Image Processing Laboratory, Universitat de Val\u00e8ncia, Valencia, Spain","institution_ids":["https://openalex.org/I16097986"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.1972,"has_fulltext":false,"cited_by_count":22,"citation_normalized_percentile":{"value":0.91679831,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"28","issue":"6","first_page":"1466","last_page":"1472"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9991999864578247,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9991999864578247,"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9980000257492065,"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/T10320","display_name":"Neural Networks and Applications","score":0.9965999722480774,"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/mathematics","display_name":"Mathematics","score":0.4515010416507721},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.374825119972229},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.34402579069137573},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.32155776023864746}],"concepts":[{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4515010416507721},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.374825119972229},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.34402579069137573},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.32155776023864746}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/tnnls.2016.2530403","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2016.2530403","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:26930695","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/26930695","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:arXiv.org:1603.02806","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1603.02806","pdf_url":"https://arxiv.org/pdf/1603.02806","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1603.02806","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1603.02806","pdf_url":"https://arxiv.org/pdf/1603.02806","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3811326624","display_name":null,"funder_award_id":"GV/2013/079","funder_id":"https://openalex.org/F4320321864","funder_display_name":"Generalitat Valenciana"},{"id":"https://openalex.org/G7860275548","display_name":null,"funder_award_id":"SEDAL-647423","funder_id":"https://openalex.org/F4320334678","funder_display_name":"European Research Council"}],"funders":[{"id":"https://openalex.org/F4320321864","display_name":"Generalitat Valenciana","ror":"https://ror.org/0097mvx21"},{"id":"https://openalex.org/F4320334678","display_name":"European Research Council","ror":"https://ror.org/0472cxd90"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":49,"referenced_works":["https://openalex.org/W96090752","https://openalex.org/W100313625","https://openalex.org/W565868953","https://openalex.org/W1491220419","https://openalex.org/W1548802052","https://openalex.org/W1577841048","https://openalex.org/W1604408772","https://openalex.org/W1999977323","https://openalex.org/W2004372301","https://openalex.org/W2008535680","https://openalex.org/W2012742969","https://openalex.org/W2018221072","https://openalex.org/W2042574171","https://openalex.org/W2049761669","https://openalex.org/W2087465675","https://openalex.org/W2089468765","https://openalex.org/W2096496077","https://openalex.org/W2096948193","https://openalex.org/W2107905252","https://openalex.org/W2109816097","https://openalex.org/W2115403315","https://openalex.org/W2118020555","https://openalex.org/W2123649031","https://openalex.org/W2129905273","https://openalex.org/W2130055251","https://openalex.org/W2134120841","https://openalex.org/W2139269942","https://openalex.org/W2140095548","https://openalex.org/W2148694408","https://openalex.org/W2149803014","https://openalex.org/W2159075893","https://openalex.org/W2167122710","https://openalex.org/W2169522260","https://openalex.org/W2547788783","https://openalex.org/W2950495522","https://openalex.org/W3098421274","https://openalex.org/W3100742177","https://openalex.org/W4205778870","https://openalex.org/W4211083646","https://openalex.org/W4230367971","https://openalex.org/W4233014035","https://openalex.org/W4248721357","https://openalex.org/W4252112654","https://openalex.org/W4252827860","https://openalex.org/W4292023222","https://openalex.org/W4376463272","https://openalex.org/W6674723449","https://openalex.org/W6680508596","https://openalex.org/W6684704092"],"related_works":["https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W4391375266","https://openalex.org/W1979597421","https://openalex.org/W2007980826","https://openalex.org/W2061531152","https://openalex.org/W3002753104","https://openalex.org/W2077600819","https://openalex.org/W2142036596","https://openalex.org/W2072657027"],"abstract_inverted_index":{"This":[0,132],"brief":[1],"addresses":[2],"two":[3],"main":[4],"issues":[5],"of":[6,17,24,35,38,44,60,76,82,161,184,230],"the":[7,15,18,22,25,36,48,61,71,77,84,112,123,156,159,162,169,175,186,208,214,228,231],"standard":[8],"kernel":[9,19,27,39,49,163,178,215,235],"entropy":[10,42,79,134],"component":[11,114],"analysis":[12,115],"(KECA)":[13],"algorithm:":[14],"optimization":[16,23],"decomposition":[20],"and":[21,117,193,222],"Gaussian":[26],"parameter.":[28],"KECA":[29,62,66,144],"roughly":[30],"reduces":[31],"to":[32,122,227],"a":[33,151],"sorting":[34],"importance":[37],"eigenvectors":[40],"by":[41,80],"instead":[43],"variance,":[45],"as":[46],"in":[47,86,91,154,190,234],"principal":[50],"components":[51],"analysis.":[52],"In":[53,106,149],"this":[54],"brief,":[55],"we":[56,173],"propose":[57],"an":[58,119],"extension":[59],"method,":[63],"named":[64],"optimized":[65,128],"(OKECA),":[67],"that":[68,137,198],"directly":[69],"extracts":[70],"optimal":[72],"features":[73,89,100,139,145],"retaining":[74],"most":[75,176,209],"data":[78],"means":[81],"compacting":[83],"information":[85],"very":[87],"few":[88],"(often":[90],"just":[92],"one":[93],"or":[94],"two).":[95],"The":[96,182],"proposed":[97],"method":[98],"produces":[99],"which":[101,126],"have":[102],"higher":[103],"expressive":[104,204],"power.":[105],"particular,":[107],"it":[108,166],"is":[109,127,158,217,224],"based":[110,218],"on":[111,219],"independent":[113],"framework,":[116],"introduces":[118],"extra":[120],"rotation":[121],"eigen":[124],"decomposition,":[125],"via":[129],"gradient-ascent":[130],"search.":[131],"maximum":[133,220],"preservation":[135],"suggests":[136],"OKECA":[138,199,223],"are":[140,188],"more":[141,203,225],"efficient":[142],"than":[143,206],"for":[146,212],"density":[147,236],"estimation.":[148,237],"addition,":[150],"critical":[152],"issue":[153],"both":[155,185],"methods":[157,187],"selection":[160,180,229],"parameter,":[164],"since":[165],"critically":[167],"affects":[168],"resulting":[170],"performance.":[171],"Here,":[172],"analyze":[174],"common":[177],"length-scale":[179,232],"criteria.":[181],"results":[183],"illustrated":[189],"different":[191],"synthetic":[192],"real":[194],"problems.":[195],"Results":[196],"show":[197],"returns":[200],"projections":[201],"with":[202],"power":[205],"KECA,":[207],"successful":[210],"rule":[211],"estimating":[213],"parameter":[216,233],"likelihood,":[221],"robust":[226]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":7},{"year":2017,"cited_by_count":4},{"year":2016,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}