{"id":"https://openalex.org/W2398887903","doi":"https://doi.org/10.1109/tcyb.2016.2565683","title":"Implementing Kernel Methods Incrementally by Incremental Nonlinear Projection Trick","display_name":"Implementing Kernel Methods Incrementally by Incremental Nonlinear Projection Trick","publication_year":2016,"publication_date":"2016-05-22","ids":{"openalex":"https://openalex.org/W2398887903","doi":"https://doi.org/10.1109/tcyb.2016.2565683","mag":"2398887903","pmid":"https://pubmed.ncbi.nlm.nih.gov/28113447"},"language":"en","primary_location":{"id":"doi:10.1109/tcyb.2016.2565683","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcyb.2016.2565683","pdf_url":null,"source":{"id":"https://openalex.org/S4210191041","display_name":"IEEE Transactions on Cybernetics","issn_l":"2168-2267","issn":["2168-2267","2168-2275"],"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 Cybernetics","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/A5084897975","display_name":"Nojun Kwak","orcid":"https://orcid.org/0000-0002-1792-0327"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Nojun Kwak","raw_affiliation_strings":["Graduate School of Convergence Science and Technology, Seoul National University, Seoul, South Korea"],"raw_orcid":"https://orcid.org/0000-0002-1792-0327","affiliations":[{"raw_affiliation_string":"Graduate School of Convergence Science and Technology, Seoul National University, Seoul, South Korea","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":["https://openalex.org/A5084897975"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.4213,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.69750966,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"47","issue":"11","first_page":"4003","last_page":"4009"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9993000030517578,"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":0.9993000030517578,"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/T10320","display_name":"Neural Networks and Applications","score":0.994700014591217,"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"}},{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.992900013923645,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/kernel-principal-component-analysis","display_name":"Kernel principal component analysis","score":0.9128040075302124},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.7984714508056641},{"id":"https://openalex.org/keywords/kernel-embedding-of-distributions","display_name":"Kernel embedding of distributions","score":0.749690592288971},{"id":"https://openalex.org/keywords/kernel-method","display_name":"Kernel method","score":0.667457640171051},{"id":"https://openalex.org/keywords/variable-kernel-density-estimation","display_name":"Variable kernel density estimation","score":0.6537328958511353},{"id":"https://openalex.org/keywords/radial-basis-function-kernel","display_name":"Radial basis function kernel","score":0.6133281588554382},{"id":"https://openalex.org/keywords/polynomial-kernel","display_name":"Polynomial kernel","score":0.6008728742599487},{"id":"https://openalex.org/keywords/kernel-fisher-discriminant-analysis","display_name":"Kernel Fisher discriminant analysis","score":0.5913713574409485},{"id":"https://openalex.org/keywords/tree-kernel","display_name":"Tree kernel","score":0.5377405285835266},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5239455699920654},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.48594796657562256},{"id":"https://openalex.org/keywords/projection","display_name":"Projection (relational algebra)","score":0.48015207052230835},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.44746172428131104},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4162457287311554},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.41437551379203796},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3810373842716217},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.0960877537727356},{"id":"https://openalex.org/keywords/discrete-mathematics","display_name":"Discrete mathematics","score":0.057052671909332275}],"concepts":[{"id":"https://openalex.org/C182335926","wikidata":"https://www.wikidata.org/wiki/Q17093020","display_name":"Kernel principal component analysis","level":4,"score":0.9128040075302124},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.7984714508056641},{"id":"https://openalex.org/C134517425","wikidata":"https://www.wikidata.org/wiki/Q16000131","display_name":"Kernel embedding of distributions","level":4,"score":0.749690592288971},{"id":"https://openalex.org/C122280245","wikidata":"https://www.wikidata.org/wiki/Q620622","display_name":"Kernel method","level":3,"score":0.667457640171051},{"id":"https://openalex.org/C195699287","wikidata":"https://www.wikidata.org/wiki/Q7915722","display_name":"Variable kernel density estimation","level":4,"score":0.6537328958511353},{"id":"https://openalex.org/C75866337","wikidata":"https://www.wikidata.org/wiki/Q7280263","display_name":"Radial basis function kernel","level":4,"score":0.6133281588554382},{"id":"https://openalex.org/C160446489","wikidata":"https://www.wikidata.org/wiki/Q7226642","display_name":"Polynomial kernel","level":4,"score":0.6008728742599487},{"id":"https://openalex.org/C181367576","wikidata":"https://www.wikidata.org/wiki/Q6394184","display_name":"Kernel Fisher discriminant analysis","level":4,"score":0.5913713574409485},{"id":"https://openalex.org/C140417398","wikidata":"https://www.wikidata.org/wiki/Q16933942","display_name":"Tree kernel","level":5,"score":0.5377405285835266},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5239455699920654},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48594796657562256},{"id":"https://openalex.org/C57493831","wikidata":"https://www.wikidata.org/wiki/Q3134666","display_name":"Projection (relational algebra)","level":2,"score":0.48015207052230835},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.44746172428131104},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4162457287311554},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.41437551379203796},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3810373842716217},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.0960877537727356},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.057052671909332275}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/tcyb.2016.2565683","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcyb.2016.2565683","pdf_url":null,"source":{"id":"https://openalex.org/S4210191041","display_name":"IEEE Transactions on Cybernetics","issn_l":"2168-2267","issn":["2168-2267","2168-2275"],"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 Cybernetics","raw_type":"journal-article"},{"id":"pmid:28113447","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/28113447","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 cybernetics","raw_type":null},{"id":"pmh:oai:s-space.snu.ac.kr:10371/206621","is_oa":false,"landing_page_url":"https://hdl.handle.net/10371/206621","pdf_url":null,"source":{"id":"https://openalex.org/S4306401345","display_name":"Seoul National University Open Repository (Seoul National University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I139264467","host_organization_name":"Seoul National University","host_organization_lineage":["https://openalex.org/I139264467"],"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":"Article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.6499999761581421,"id":"https://metadata.un.org/sdg/10"}],"awards":[{"id":"https://openalex.org/G1017966453","display_name":null,"funder_award_id":"KRF-2013006599","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"}],"funders":[{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"},{"id":"https://openalex.org/F4320323890","display_name":"Korea Creative Content Agency","ror":"https://ror.org/036vyg793"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1489867037","https://openalex.org/W1496864517","https://openalex.org/W1497057245","https://openalex.org/W1510073064","https://openalex.org/W1560724230","https://openalex.org/W1984421104","https://openalex.org/W1988068451","https://openalex.org/W2019533369","https://openalex.org/W2033244207","https://openalex.org/W2041797434","https://openalex.org/W2084812512","https://openalex.org/W2085044339","https://openalex.org/W2092193054","https://openalex.org/W2105608756","https://openalex.org/W2111150210","https://openalex.org/W2112545207","https://openalex.org/W2116810533","https://openalex.org/W2118495562","https://openalex.org/W2121085248","https://openalex.org/W2127125214","https://openalex.org/W2133140216","https://openalex.org/W2137557016","https://openalex.org/W2144414190","https://openalex.org/W2150590096","https://openalex.org/W2160840682","https://openalex.org/W2164071167","https://openalex.org/W3144619878","https://openalex.org/W6680634009","https://openalex.org/W6681291431"],"related_works":["https://openalex.org/W3013206934","https://openalex.org/W3100948281","https://openalex.org/W4311138679","https://openalex.org/W3123056048","https://openalex.org/W1983263273","https://openalex.org/W4291669689","https://openalex.org/W2515338903","https://openalex.org/W2610521515","https://openalex.org/W1509134351","https://openalex.org/W2108995755"],"abstract_inverted_index":{"Recently,":[0],"the":[1,37,73,80,83,91,97,100,103,122,128],"nonlinear":[2],"projection":[3],"trick":[4],"(NPT)":[5],"was":[6],"introduced":[7],"enabling":[8],"direct":[9],"computation":[10],"of":[11,13,72,99,121,127,139,161],"coordinates":[12,98,104],"samples":[14,63],"in":[15,86,112],"a":[16,31,118],"reproducing":[17],"kernel":[18,32,40,55,119,140,144,148,153,162],"Hilbert":[19],"space.":[20],"With":[21],"NPT,":[22],"any":[23,113],"machine":[24],"learning":[25],"algorithm":[26],"can":[27,108],"be":[28,48,58,110],"extended":[29],"to":[30,47,116,135],"version":[33,71,120],"without":[34],"relying":[35],"on":[36,79],"so":[38],"called":[39],"trick.":[41],"However,":[42],"NPT":[43,74,87],"is":[44,76,88,130],"inherently":[45],"difficult":[46],"implemented":[49],"incrementally":[50],"because":[51],"an":[52,69],"ever":[53],"increasing":[54],"matrix":[56,163],"should":[57],"treated":[59],"as":[60],"additional":[61],"training":[62],"are":[64,157],"introduced.":[65],"In":[66],"this":[67],"paper,":[68],"incremental":[70,114,123,137],"(INPT)":[75],"proposed":[77,92],"based":[78],"observation":[81],"that":[82],"centerization":[84],"step":[85],"unnecessary.":[89],"Because":[90],"INPT":[93,107,129],"does":[94],"not":[95],"change":[96],"old":[101],"data,":[102],"obtained":[105],"by":[106,132],"directly":[109],"used":[111],"methods":[115,141],"implement":[117,136],"methods.":[124],"The":[125],"effectiveness":[126],"shown":[131],"applying":[133],"it":[134],"versions":[138],"such":[142],"as,":[143],"singular":[145],"value":[146],"decomposition,":[147],"principal":[149],"component":[150],"analysis,":[151],"and":[152,167],"discriminant":[154],"analysis":[155],"which":[156],"utilized":[158],"for":[159],"problems":[160],"reconstruction,":[164],"letter":[165],"classification,":[166],"face":[168],"image":[169],"retrieval,":[170],"respectively.":[171]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":4},{"year":2018,"cited_by_count":1},{"year":2016,"cited_by_count":1}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}