{"id":"https://openalex.org/W2469920026","doi":"https://doi.org/10.1109/tip.2016.2587119","title":"Multiple Kernel Sparse Representation based Orthogonal Discriminative Projection and Its Cost-Sensitive Extension","display_name":"Multiple Kernel Sparse Representation based Orthogonal Discriminative Projection and Its Cost-Sensitive Extension","publication_year":2016,"publication_date":"2016-01-01","ids":{"openalex":"https://openalex.org/W2469920026","doi":"https://doi.org/10.1109/tip.2016.2587119","mag":"2469920026","pmid":"https://pubmed.ncbi.nlm.nih.gov/27392352"},"language":"en","primary_location":{"id":"doi:10.1109/tip.2016.2587119","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2016.2587119","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"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 Image Processing","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/A5074863605","display_name":"Guoqing Zhang","orcid":"https://orcid.org/0000-0002-8741-8607"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Guoqing Zhang","raw_affiliation_strings":["School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110740604","display_name":"Huaijiang Sun","orcid":null},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huaijiang Sun","raw_affiliation_strings":["School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042140417","display_name":"Guiyu Xia","orcid":"https://orcid.org/0000-0003-4909-0361"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guiyu Xia","raw_affiliation_strings":["School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5034434932","display_name":"Quansen Sun","orcid":"https://orcid.org/0000-0001-6019-1986"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Quansen Sun","raw_affiliation_strings":["School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China","institution_ids":["https://openalex.org/I36399199"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5074863605"],"corresponding_institution_ids":["https://openalex.org/I36399199"],"apc_list":null,"apc_paid":null,"fwci":2.5051,"has_fulltext":false,"cited_by_count":23,"citation_normalized_percentile":{"value":0.93023646,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"25","issue":"9","first_page":"1","last_page":"1"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.996999979019165,"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":0.996999979019165,"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9933000206947327,"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/T13731","display_name":"Advanced Computing and Algorithms","score":0.9929999709129333,"subfield":{"id":"https://openalex.org/subfields/3322","display_name":"Urban Studies"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6355056762695312},{"id":"https://openalex.org/keywords/kernel-embedding-of-distributions","display_name":"Kernel embedding of distributions","score":0.6344479918479919},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.6190444827079773},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6013425588607788},{"id":"https://openalex.org/keywords/radial-basis-function-kernel","display_name":"Radial basis function kernel","score":0.5815834403038025},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5451551675796509},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.5388516783714294},{"id":"https://openalex.org/keywords/multiple-kernel-learning","display_name":"Multiple kernel learning","score":0.5193951725959778},{"id":"https://openalex.org/keywords/kernel-method","display_name":"Kernel method","score":0.5179040431976318},{"id":"https://openalex.org/keywords/kernel-principal-component-analysis","display_name":"Kernel principal component analysis","score":0.5120595097541809},{"id":"https://openalex.org/keywords/tree-kernel","display_name":"Tree kernel","score":0.5060076117515564},{"id":"https://openalex.org/keywords/variable-kernel-density-estimation","display_name":"Variable kernel density estimation","score":0.4963741898536682},{"id":"https://openalex.org/keywords/sparse-approximation","display_name":"Sparse approximation","score":0.4404885470867157},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.3893097937107086},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3351893424987793},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.31832289695739746}],"concepts":[{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6355056762695312},{"id":"https://openalex.org/C134517425","wikidata":"https://www.wikidata.org/wiki/Q16000131","display_name":"Kernel embedding of distributions","level":4,"score":0.6344479918479919},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.6190444827079773},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6013425588607788},{"id":"https://openalex.org/C75866337","wikidata":"https://www.wikidata.org/wiki/Q7280263","display_name":"Radial basis function kernel","level":4,"score":0.5815834403038025},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5451551675796509},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.5388516783714294},{"id":"https://openalex.org/C2776879701","wikidata":"https://www.wikidata.org/wiki/Q25048660","display_name":"Multiple kernel learning","level":4,"score":0.5193951725959778},{"id":"https://openalex.org/C122280245","wikidata":"https://www.wikidata.org/wiki/Q620622","display_name":"Kernel method","level":3,"score":0.5179040431976318},{"id":"https://openalex.org/C182335926","wikidata":"https://www.wikidata.org/wiki/Q17093020","display_name":"Kernel principal component analysis","level":4,"score":0.5120595097541809},{"id":"https://openalex.org/C140417398","wikidata":"https://www.wikidata.org/wiki/Q16933942","display_name":"Tree kernel","level":5,"score":0.5060076117515564},{"id":"https://openalex.org/C195699287","wikidata":"https://www.wikidata.org/wiki/Q7915722","display_name":"Variable kernel density estimation","level":4,"score":0.4963741898536682},{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.4404885470867157},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3893097937107086},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3351893424987793},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.31832289695739746},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tip.2016.2587119","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2016.2587119","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"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 Image Processing","raw_type":"journal-article"},{"id":"pmid:27392352","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/27392352","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 image processing : a publication of the IEEE Signal Processing Society","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.75,"id":"https://metadata.un.org/sdg/10"}],"awards":[{"id":"https://openalex.org/G1713501938","display_name":null,"funder_award_id":"61273251","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5900045971","display_name":null,"funder_award_id":"61401209","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"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":56,"referenced_works":["https://openalex.org/W191001584","https://openalex.org/W1591385104","https://openalex.org/W1598764398","https://openalex.org/W1808256548","https://openalex.org/W1915109052","https://openalex.org/W1964749215","https://openalex.org/W1977806565","https://openalex.org/W1991359796","https://openalex.org/W2001141328","https://openalex.org/W2004465977","https://openalex.org/W2006793117","https://openalex.org/W2029147317","https://openalex.org/W2033419168","https://openalex.org/W2053186076","https://openalex.org/W2054502547","https://openalex.org/W2070127246","https://openalex.org/W2073039305","https://openalex.org/W2085192601","https://openalex.org/W2094174855","https://openalex.org/W2094684700","https://openalex.org/W2100659887","https://openalex.org/W2104294146","https://openalex.org/W2108995755","https://openalex.org/W2109743529","https://openalex.org/W2117553576","https://openalex.org/W2120396754","https://openalex.org/W2120552947","https://openalex.org/W2121033924","https://openalex.org/W2121647436","https://openalex.org/W2123961273","https://openalex.org/W2125874614","https://openalex.org/W2129812935","https://openalex.org/W2138451337","https://openalex.org/W2142848040","https://openalex.org/W2145295623","https://openalex.org/W2149861038","https://openalex.org/W2156505030","https://openalex.org/W2157558673","https://openalex.org/W2158281641","https://openalex.org/W2163406054","https://openalex.org/W2163771264","https://openalex.org/W2169278871","https://openalex.org/W2170356051","https://openalex.org/W2214725774","https://openalex.org/W2538008885","https://openalex.org/W2994340921","https://openalex.org/W3005272312","https://openalex.org/W3148981562","https://openalex.org/W6635804413","https://openalex.org/W6640140148","https://openalex.org/W6641446668","https://openalex.org/W6678059867","https://openalex.org/W6682865783","https://openalex.org/W6682921674","https://openalex.org/W6684134493","https://openalex.org/W6685016619"],"related_works":["https://openalex.org/W3100948281","https://openalex.org/W3013206934","https://openalex.org/W1983263273","https://openalex.org/W3123056048","https://openalex.org/W4311138679","https://openalex.org/W4291669689","https://openalex.org/W2071590642","https://openalex.org/W2371064519","https://openalex.org/W1976730005","https://openalex.org/W2001173190"],"abstract_inverted_index":{"Sparse":[0],"representation-based":[1,44,128,144],"classification":[2],"(SRC)":[3],"has":[4,87],"been":[5,88],"developed":[6],"and":[7,53,69,75,130,158,180],"shown":[8],"great":[9],"potential":[10],"for":[11,84,213],"real-world":[12],"application.":[13],"Based":[14],"on":[15,222],"SRC,":[16],"Yang":[17],"et":[18],"al.":[19],"devised":[20],"an":[21],"SRC":[22,52,85],"steered":[23],"discriminative":[24,146],"projection":[25,147,156],"(SRC-DP)":[26],"method.":[27,148,210,226],"However,":[28,100],"as":[29,135],"a":[30,48,65,92,95,123,136,140,155,159,190],"linear":[31],"algorithm,":[32],"SRC-DP":[33],"cannot":[34],"handle":[35],"the":[36,56,62,72,104,110,115,163,170,174,181,198,207,214,231,234,240],"data":[37],"with":[38,239],"highly":[39],"nonlinear":[40],"distribution.":[41],"Kernel":[42],"sparse":[43,127,143],"classifier":[45],"(KSRC)":[46],"is":[47,78,178,185],"non-linear":[49],"extension":[50],"of":[51,58,64,71,97,233],"can":[54,217],"remedy":[55],"drawback":[57],"SRC.":[59],"KSRC":[60],"requires":[61],"use":[63,133],"predetermined":[66],"kernel":[67,73,82,93,116,126,142,161],"function":[68,74],"selection":[70],"its":[76],"parameters":[77],"difficult.":[79],"Recently,":[80],"multiple":[81,125,141],"learning":[83,114,154],"(MKL-SRC)":[86],"proposed":[89,150,215,235],"to":[90,138,188],"learn":[91],"from":[94,162],"set":[96],"base":[98,165],"kernels.":[99],"MKL-SRC":[101],"only":[102],"considers":[103],"within-class":[105,182],"reconstruction":[106,176,183],"residual":[107,177,184],"while":[108],"ignoring":[109],"between-class":[111,175],"relationship,":[112],"when":[113,237],"weights.":[117],"In":[118],"this":[119],"paper,":[120],"we":[121,132,202],"propose":[122],"novel":[124],"classifier,":[129],"then":[131],"it":[134],"criterion":[137],"design":[139],"orthogonal":[145],"The":[149,211],"algorithm":[151,236],"aims":[152],"at":[153],"matrix":[157],"corresponding":[160],"given":[164],"kernels":[166],"such":[167],"that":[168],"in":[169,197],"low":[171],"dimension":[172],"subspace":[173],"maximized":[179],"minimized.":[186],"Furthermore,":[187],"achieve":[189],"minimum":[191],"overall":[192],"loss":[193],"by":[194],"performing":[195],"recognition":[196],"learned":[199],"low-dimensional":[200],"subspace,":[201],"introduce":[203],"cost":[204],"information":[205],"into":[206],"dimensionality":[208],"reduction":[209],"solutions":[212],"method":[216],"be":[218],"efficiently":[219],"found":[220],"based":[221],"trace":[223],"ratio":[224],"optimization":[225],"Extensive":[227],"experimental":[228],"results":[229],"demonstrate":[230],"superiority":[232],"compared":[238],"state-of-the-art":[241],"methods.":[242]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":6},{"year":2018,"cited_by_count":6},{"year":2017,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}