{"id":"https://openalex.org/W2783376202","doi":"https://doi.org/10.1109/tnnls.2017.2785324","title":"Modified Sparse Linear-Discriminant Analysis via Nonconvex Penalties","display_name":"Modified Sparse Linear-Discriminant Analysis via Nonconvex Penalties","publication_year":2018,"publication_date":"2018-01-15","ids":{"openalex":"https://openalex.org/W2783376202","doi":"https://doi.org/10.1109/tnnls.2017.2785324","mag":"2783376202","pmid":"https://pubmed.ncbi.nlm.nih.gov/29994754"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2017.2785324","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2017.2785324","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/A5033196884","display_name":"Jia Cai","orcid":"https://orcid.org/0000-0001-8942-8668"},"institutions":[{"id":"https://openalex.org/I201459984","display_name":"Guangdong University Of Finances and Economics","ror":"https://ror.org/0459pv085","country_code":"CN","type":"education","lineage":["https://openalex.org/I201459984"]},{"id":"https://openalex.org/I4210149618","display_name":"Guangdong University of Finance","ror":"https://ror.org/04grzdh47","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210149618"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jia Cai","raw_affiliation_strings":["School of Statistics and Mathematics, Guangdong University of Finance and Economics, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0001-8942-8668","affiliations":[{"raw_affiliation_string":"School of Statistics and Mathematics, Guangdong University of Finance and Economics, Guangzhou, China","institution_ids":["https://openalex.org/I201459984","https://openalex.org/I4210149618"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5026169938","display_name":"Xiaolin Huang","orcid":"https://orcid.org/0000-0003-4285-6520"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaolin Huang","raw_affiliation_strings":["Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0003-4285-6520","affiliations":[{"raw_affiliation_string":"Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5033196884"],"corresponding_institution_ids":["https://openalex.org/I201459984","https://openalex.org/I4210149618"],"apc_list":null,"apc_paid":null,"fwci":2.705,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":{"value":0.89245553,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"29","issue":"10","first_page":"4957","last_page":"4966"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9998999834060669,"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/T10057","display_name":"Face and Expression Recognition","score":0.9972000122070312,"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/T12676","display_name":"Machine Learning and ELM","score":0.9901999831199646,"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/linear-discriminant-analysis","display_name":"Linear discriminant analysis","score":0.7248379588127136},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5399764180183411},{"id":"https://openalex.org/keywords/discriminant","display_name":"Discriminant","score":0.44726601243019104},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4388121962547302},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.36159148812294006}],"concepts":[{"id":"https://openalex.org/C69738355","wikidata":"https://www.wikidata.org/wiki/Q1228929","display_name":"Linear discriminant analysis","level":2,"score":0.7248379588127136},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5399764180183411},{"id":"https://openalex.org/C78397625","wikidata":"https://www.wikidata.org/wiki/Q192487","display_name":"Discriminant","level":2,"score":0.44726601243019104},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4388121962547302},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.36159148812294006}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2017.2785324","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2017.2785324","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:29994754","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/29994754","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}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6499999761581421,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G7723117339","display_name":null,"funder_award_id":"11401112","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8555058780","display_name":null,"funder_award_id":"61603248","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/F4320322725","display_name":"China Scholarship Council","ror":"https://ror.org/04atp4p48"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":51,"referenced_works":["https://openalex.org/W20027422","https://openalex.org/W1906972028","https://openalex.org/W1915008591","https://openalex.org/W1966701961","https://openalex.org/W1970814699","https://openalex.org/W1973397215","https://openalex.org/W1987820147","https://openalex.org/W1989834782","https://openalex.org/W1997841190","https://openalex.org/W1998615394","https://openalex.org/W2004544971","https://openalex.org/W2009596443","https://openalex.org/W2012352340","https://openalex.org/W2015418199","https://openalex.org/W2020390700","https://openalex.org/W2022086975","https://openalex.org/W2027717478","https://openalex.org/W2036796028","https://openalex.org/W2056201402","https://openalex.org/W2062125287","https://openalex.org/W2065321782","https://openalex.org/W2074682976","https://openalex.org/W2079130430","https://openalex.org/W2084978503","https://openalex.org/W2089322632","https://openalex.org/W2103215959","https://openalex.org/W2116148865","https://openalex.org/W2122825543","https://openalex.org/W2128659236","https://openalex.org/W2129131372","https://openalex.org/W2134403207","https://openalex.org/W2135346934","https://openalex.org/W2151693816","https://openalex.org/W2155423555","https://openalex.org/W2157875785","https://openalex.org/W2318949783","https://openalex.org/W2319660501","https://openalex.org/W2339611261","https://openalex.org/W2427656690","https://openalex.org/W2474352580","https://openalex.org/W2544383265","https://openalex.org/W2565703388","https://openalex.org/W3005272312","https://openalex.org/W4210650935","https://openalex.org/W4238240379","https://openalex.org/W4244000367","https://openalex.org/W6600830112","https://openalex.org/W6679735670","https://openalex.org/W6684134493","https://openalex.org/W6729192012","https://openalex.org/W6731309402"],"related_works":["https://openalex.org/W2350751952","https://openalex.org/W1999647744","https://openalex.org/W2362114017","https://openalex.org/W3147024994","https://openalex.org/W2063246903","https://openalex.org/W2374055396","https://openalex.org/W1978302214","https://openalex.org/W2021817983","https://openalex.org/W2104382484","https://openalex.org/W3008559849"],"abstract_inverted_index":{"This":[0],"paper":[1],"considers":[2],"the":[3,9,14,22,33,43,48,58,73,78,95,110],"linear-discriminant":[4],"analysis":[5,68],"(LDA)":[6],"problem":[7],"in":[8,12,32],"undersampled":[10],"situation,":[11],"which":[13],"number":[15,23],"of":[16,24,35,42,47,57],"features":[17],"is":[18,26,29],"very":[19],"large":[20],"and":[21,77,98,114],"observations":[25],"limited.":[27],"Sparsity":[28],"often":[30],"incorporated":[31],"solution":[34],"LDA":[36,51,83,105],"to":[37],"make":[38],"a":[39,92],"well":[40],"interpretation":[41],"results.":[44],"However,":[45],"most":[46],"existing":[49],"sparse":[50],"algorithms":[52,106],"pursue":[53],"sparsity":[54],"by":[55],"means":[56],"$\\ell":[59,74,80,96,99],"_{1}$":[60,81,100],"-norm.":[61],"In":[62],"this":[63],"paper,":[64],"we":[65],"give":[66],"elaborate":[67],"for":[69],"nonconvex":[70,103],"penalties,":[71],"including":[72],"_{0}$":[75,97],"-based":[76,82],"sorted":[79],"methods.":[84],"The":[85],"latter":[86],"one":[87],"can":[88],"be":[89],"regarded":[90],"as":[91],"bridge":[93],"between":[94],"penalties.":[101],"These":[102],"penalty-based":[104],"are":[107],"evaluated":[108],"on":[109,121],"gene":[111],"expression":[112],"array":[113],"face":[115],"database,":[116],"showing":[117],"high":[118],"classification":[119],"accuracy":[120],"real-world":[122],"problems.":[123]},"counts_by_year":[{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}