{"id":"https://openalex.org/W2166693468","doi":"https://doi.org/10.1109/tnnls.2013.2281428","title":"L1-Norm Kernel Discriminant Analysis Via Bayes Error Bound Optimization for Robust Feature Extraction","display_name":"L1-Norm Kernel Discriminant Analysis Via Bayes Error Bound Optimization for Robust Feature Extraction","publication_year":2013,"publication_date":"2013-10-03","ids":{"openalex":"https://openalex.org/W2166693468","doi":"https://doi.org/10.1109/tnnls.2013.2281428","mag":"2166693468","pmid":"https://pubmed.ncbi.nlm.nih.gov/24807955"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2013.2281428","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2013.2281428","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/A5029771864","display_name":"Wenming Zheng","orcid":"https://orcid.org/0000-0002-7764-5179"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenming Zheng","raw_affiliation_strings":["Southeast University, Key Laboratory of Child Development and Learning Science, Research Center for Learning Science, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Southeast University, Key Laboratory of Child Development and Learning Science, Research Center for Learning Science, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016399094","display_name":"Zhouchen Lin","orcid":"https://orcid.org/0000-0003-1493-7569"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhouchen Lin","raw_affiliation_strings":["Peking University, Key Laboratory of Machine Perception, School of Electronics Engineering and Computer Science, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Peking University, Key Laboratory of Machine Perception, School of Electronics Engineering and Computer Science, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5018364879","display_name":"Haixian Wang","orcid":"https://orcid.org/0000-0001-8220-9737"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haixian Wang","raw_affiliation_strings":["Southeast University, Key Laboratory of Child Development and Learning Science, Research Center for Learning Science, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Southeast University, Key Laboratory of Child Development and Learning Science, Research Center for Learning Science, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":4.6237,"has_fulltext":false,"cited_by_count":76,"citation_normalized_percentile":{"value":0.95618493,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":"25","issue":"4","first_page":"793","last_page":"805"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9975000023841858,"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":0.9975000023841858,"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/T10876","display_name":"Fault Detection and Control Systems","score":0.9975000023841858,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"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/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9955999851226807,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/kernel-fisher-discriminant-analysis","display_name":"Kernel Fisher discriminant analysis","score":0.8274494409561157},{"id":"https://openalex.org/keywords/linear-discriminant-analysis","display_name":"Linear discriminant analysis","score":0.7503235936164856},{"id":"https://openalex.org/keywords/optimal-discriminant-analysis","display_name":"Optimal discriminant analysis","score":0.5931732058525085},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5663385391235352},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5462223887443542},{"id":"https://openalex.org/keywords/norm","display_name":"Norm (philosophy)","score":0.4826641380786896},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.4613509178161621},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.45667171478271484},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.4565869867801666},{"id":"https://openalex.org/keywords/optimization-problem","display_name":"Optimization problem","score":0.45570996403694153},{"id":"https://openalex.org/keywords/convex-optimization","display_name":"Convex optimization","score":0.4386182427406311},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3671140670776367},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.3398764133453369},{"id":"https://openalex.org/keywords/regular-polygon","display_name":"Regular polygon","score":0.1896229386329651}],"concepts":[{"id":"https://openalex.org/C181367576","wikidata":"https://www.wikidata.org/wiki/Q6394184","display_name":"Kernel Fisher discriminant analysis","level":4,"score":0.8274494409561157},{"id":"https://openalex.org/C69738355","wikidata":"https://www.wikidata.org/wiki/Q1228929","display_name":"Linear discriminant analysis","level":2,"score":0.7503235936164856},{"id":"https://openalex.org/C104500394","wikidata":"https://www.wikidata.org/wiki/Q17104912","display_name":"Optimal discriminant analysis","level":3,"score":0.5931732058525085},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5663385391235352},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5462223887443542},{"id":"https://openalex.org/C191795146","wikidata":"https://www.wikidata.org/wiki/Q3878446","display_name":"Norm (philosophy)","level":2,"score":0.4826641380786896},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.4613509178161621},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45667171478271484},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.4565869867801666},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.45570996403694153},{"id":"https://openalex.org/C157972887","wikidata":"https://www.wikidata.org/wiki/Q463359","display_name":"Convex optimization","level":3,"score":0.4386182427406311},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3671140670776367},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3398764133453369},{"id":"https://openalex.org/C112680207","wikidata":"https://www.wikidata.org/wiki/Q714886","display_name":"Regular polygon","level":2,"score":0.1896229386329651},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/tnnls.2013.2281428","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2013.2281428","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:24807955","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/24807955","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:10.1.1.676.7839","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.676.7839","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cis.pku.edu.cn/faculty/vision/zlin/Publications/2014-TNNLS-L1-KDA.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7400000095367432,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G2344363859","display_name":null,"funder_award_id":"BK20130020","funder_id":"https://openalex.org/F4320322769","funder_display_name":"Natural Science Foundation of Jiangsu Province"},{"id":"https://openalex.org/G2636727136","display_name":null,"funder_award_id":"61073137","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3875471163","display_name":"\u57fa\u4e8e\u89c6\u9891\u5206\u6790\u7684\u513f\u7ae5\u884c\u4e3a\u7814\u7a76","funder_award_id":"61231002","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8069300600","display_name":null,"funder_award_id":"2011CB302202","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program 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/F4320322769","display_name":"Natural Science Foundation of Jiangsu Province","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W83066537","https://openalex.org/W1510073064","https://openalex.org/W1592941960","https://openalex.org/W1770825568","https://openalex.org/W1975900269","https://openalex.org/W1992633833","https://openalex.org/W2008277111","https://openalex.org/W2009596443","https://openalex.org/W2021012145","https://openalex.org/W2027717478","https://openalex.org/W2036926179","https://openalex.org/W2052059892","https://openalex.org/W2053090063","https://openalex.org/W2053585103","https://openalex.org/W2074596973","https://openalex.org/W2101117936","https://openalex.org/W2113713615","https://openalex.org/W2113812158","https://openalex.org/W2121647436","https://openalex.org/W2123157895","https://openalex.org/W2124161253","https://openalex.org/W2130418330","https://openalex.org/W2132549764","https://openalex.org/W2135081536","https://openalex.org/W2135346934","https://openalex.org/W2140095548","https://openalex.org/W2151416140","https://openalex.org/W2163055872","https://openalex.org/W2164071167","https://openalex.org/W2913141361","https://openalex.org/W3009784374","https://openalex.org/W4242209908","https://openalex.org/W6635516332","https://openalex.org/W6675479683","https://openalex.org/W6678385540","https://openalex.org/W6679749283","https://openalex.org/W6683855484"],"related_works":["https://openalex.org/W2386228546","https://openalex.org/W2086055175","https://openalex.org/W2538559652","https://openalex.org/W2354349698","https://openalex.org/W2371167124","https://openalex.org/W1562318760","https://openalex.org/W2043814783","https://openalex.org/W2129407254","https://openalex.org/W2127478267","https://openalex.org/W2064257630"],"abstract_inverted_index":{"A":[0],"novel":[1,84],"discriminant":[2,23,53,60,143],"analysis":[3,61,144],"criterion":[4],"is":[5,32,88,98,110],"derived":[6],"in":[7,81,95,165],"this":[8,113],"paper":[9],"under":[10],"the":[11,20,25,29,33,48,51,71,92,119,125,132,140,159,162,168],"theoretical":[12],"framework":[13],"of":[14,28,35,134,161],"Bayes":[15],"optimality.":[16],"In":[17],"contrast":[18],"to":[19,47,99,112,122,157],"conventional":[21],"Fisher's":[22],"criterion,":[24,54],"major":[26],"novelty":[27],"proposed":[30,139,163],"one":[31],"use":[34,133],"L1":[36],"norm":[37],"rather":[38],"than":[39],"L2":[40],"norm,":[41],"which":[42,82],"makes":[43],"it":[44],"less":[45],"sensitive":[46],"outliers.":[49],"With":[50],"L1-norm":[52,141],"we":[55,75,116],"propose":[56,76],"a":[57,83,102,107],"new":[58],"linear":[59,65],"(L1-LDA)":[62],"method":[63,121,164],"for":[64],"feature":[66,128],"extraction":[67,129],"problem.":[68,114],"To":[69],"solve":[70,101],"L1-LDA":[72,120],"optimization":[73,93],"problem,":[74],"an":[77],"efficient":[78],"iterative":[79],"algorithm,":[80],"surrogate":[85],"convex":[86,103],"function":[87],"introduced":[89],"such":[90],"that":[91],"problem":[94,105],"each":[96],"iteration":[97],"simply":[100],"programming":[104],"and":[106,137,151],"close-form":[108],"solution":[109],"guaranteed":[111],"Moreover,":[115],"also":[117],"generalize":[118],"deal":[123],"with":[124,167],"nonlinear":[126],"robust":[127],"problems":[130],"via":[131],"kernel":[135,142],"trick,":[136],"hereafter":[138],"(L1-KDA)":[145],"method.":[146],"Extensive":[147],"experiments":[148],"on":[149],"simulated":[150],"real":[152],"data":[153],"sets":[154],"are":[155],"conducted":[156],"evaluate":[158],"effectiveness":[160],"comparing":[166],"state-of-the-art":[169],"methods.":[170]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":6},{"year":2019,"cited_by_count":18},{"year":2018,"cited_by_count":9},{"year":2017,"cited_by_count":6},{"year":2016,"cited_by_count":13},{"year":2015,"cited_by_count":3},{"year":2014,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}