{"id":"https://openalex.org/W2097495946","doi":"https://doi.org/10.1109/icdm.2003.1250926","title":"Efficient nonlinear dimension reduction for clustered data using kernel functions","display_name":"Efficient nonlinear dimension reduction for clustered data using kernel functions","publication_year":2004,"publication_date":"2004-03-30","ids":{"openalex":"https://openalex.org/W2097495946","doi":"https://doi.org/10.1109/icdm.2003.1250926","mag":"2097495946"},"language":"en","primary_location":{"id":"doi:10.1109/icdm.2003.1250926","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icdm.2003.1250926","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Third IEEE International Conference on Data Mining","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"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/A5027621863","display_name":"C.H. Park","orcid":null},"institutions":[{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"C.H. Park","raw_affiliation_strings":["Department of Computer Science and Engineering, University of Minnesota, Minneapolis, MN, USA","Dept. of Comput. Sci. & Eng., Minnesota Univ., Minneapolis, MN, USA#TAB#"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, University of Minnesota, Minneapolis, MN, USA","institution_ids":["https://openalex.org/I130238516"]},{"raw_affiliation_string":"Dept. of Comput. Sci. & Eng., Minnesota Univ., Minneapolis, MN, USA#TAB#","institution_ids":["https://openalex.org/I130238516"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5047133445","display_name":"H. Park","orcid":null},"institutions":[{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"H. Park","raw_affiliation_strings":["Department of Computer Science and Engineering, University of Minnesota, Minneapolis, MN, USA","Dept. of Comput. Sci. & Eng., Minnesota Univ., Minneapolis, MN, USA#TAB#"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, University of Minnesota, Minneapolis, MN, USA","institution_ids":["https://openalex.org/I130238516"]},{"raw_affiliation_string":"Dept. of Comput. Sci. & Eng., Minnesota Univ., Minneapolis, MN, USA#TAB#","institution_ids":["https://openalex.org/I130238516"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5027621863"],"corresponding_institution_ids":["https://openalex.org/I130238516"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.15120128,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"243","last_page":"250"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9997000098228455,"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":0.9997000098228455,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9955000281333923,"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/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9927999973297119,"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/orthonormal-basis","display_name":"Orthonormal basis","score":0.8731884956359863},{"id":"https://openalex.org/keywords/centroid","display_name":"Centroid","score":0.8034513592720032},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.7159944772720337},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6196108460426331},{"id":"https://openalex.org/keywords/kernel-principal-component-analysis","display_name":"Kernel principal component analysis","score":0.5872999429702759},{"id":"https://openalex.org/keywords/basis-function","display_name":"Basis function","score":0.5680147409439087},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.5622525215148926},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.5527231097221375},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.5511044859886169},{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.5166809558868408},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5126875638961792},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4970429241657257},{"id":"https://openalex.org/keywords/kernel-embedding-of-distributions","display_name":"Kernel embedding of distributions","score":0.49439549446105957},{"id":"https://openalex.org/keywords/kernel-method","display_name":"Kernel method","score":0.47027069330215454},{"id":"https://openalex.org/keywords/radial-basis-function-kernel","display_name":"Radial basis function kernel","score":0.4682028889656067},{"id":"https://openalex.org/keywords/variable-kernel-density-estimation","display_name":"Variable kernel density estimation","score":0.44477954506874084},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.44348886609077454},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.44225892424583435},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.43008238077163696},{"id":"https://openalex.org/keywords/transformation","display_name":"Transformation (genetics)","score":0.42468202114105225},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.25510111451148987},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.09707304835319519},{"id":"https://openalex.org/keywords/discrete-mathematics","display_name":"Discrete mathematics","score":0.07233700156211853},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.06161630153656006}],"concepts":[{"id":"https://openalex.org/C5806529","wikidata":"https://www.wikidata.org/wiki/Q2365325","display_name":"Orthonormal basis","level":2,"score":0.8731884956359863},{"id":"https://openalex.org/C146599234","wikidata":"https://www.wikidata.org/wiki/Q511093","display_name":"Centroid","level":2,"score":0.8034513592720032},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.7159944772720337},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6196108460426331},{"id":"https://openalex.org/C182335926","wikidata":"https://www.wikidata.org/wiki/Q17093020","display_name":"Kernel principal component analysis","level":4,"score":0.5872999429702759},{"id":"https://openalex.org/C5917680","wikidata":"https://www.wikidata.org/wiki/Q2621825","display_name":"Basis function","level":2,"score":0.5680147409439087},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.5622525215148926},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.5527231097221375},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.5511044859886169},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.5166809558868408},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5126875638961792},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4970429241657257},{"id":"https://openalex.org/C134517425","wikidata":"https://www.wikidata.org/wiki/Q16000131","display_name":"Kernel embedding of distributions","level":4,"score":0.49439549446105957},{"id":"https://openalex.org/C122280245","wikidata":"https://www.wikidata.org/wiki/Q620622","display_name":"Kernel method","level":3,"score":0.47027069330215454},{"id":"https://openalex.org/C75866337","wikidata":"https://www.wikidata.org/wiki/Q7280263","display_name":"Radial basis function kernel","level":4,"score":0.4682028889656067},{"id":"https://openalex.org/C195699287","wikidata":"https://www.wikidata.org/wiki/Q7915722","display_name":"Variable kernel density estimation","level":4,"score":0.44477954506874084},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.44348886609077454},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.44225892424583435},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.43008238077163696},{"id":"https://openalex.org/C204241405","wikidata":"https://www.wikidata.org/wiki/Q461499","display_name":"Transformation (genetics)","level":3,"score":0.42468202114105225},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.25510111451148987},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.09707304835319519},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.07233700156211853},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.06161630153656006},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icdm.2003.1250926","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icdm.2003.1250926","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Third IEEE International Conference on Data Mining","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320309636","display_name":"University of Minnesota","ror":"https://ror.org/03grvy078"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W91227773","https://openalex.org/W1535854520","https://openalex.org/W1563088657","https://openalex.org/W1563229119","https://openalex.org/W1576520375","https://openalex.org/W1770825568","https://openalex.org/W2041657594","https://openalex.org/W2083249151","https://openalex.org/W2088032561","https://openalex.org/W2096925994","https://openalex.org/W2108146080","https://openalex.org/W2113815127","https://openalex.org/W2135346934","https://openalex.org/W2139212933","https://openalex.org/W2140095548","https://openalex.org/W2146820706","https://openalex.org/W2150796457","https://openalex.org/W2798909945","https://openalex.org/W2799061466","https://openalex.org/W3193477162","https://openalex.org/W4230946174","https://openalex.org/W6634442568","https://openalex.org/W6674732917","https://openalex.org/W6676016610"],"related_works":["https://openalex.org/W2393746448","https://openalex.org/W1984421104","https://openalex.org/W2071590642","https://openalex.org/W2366185040","https://openalex.org/W2127229869","https://openalex.org/W2512565647","https://openalex.org/W2027376491","https://openalex.org/W2384322977","https://openalex.org/W2612521689","https://openalex.org/W2962967634"],"abstract_inverted_index":{"We":[0],"propose":[1],"a":[2,29,33,39,79],"nonlinear":[3,18,98],"feature":[4,30,51,75],"extraction":[5],"method":[6,61,93],"which":[7],"is":[8,20,94],"based":[9,42],"on":[10,43],"centroids":[11,48,72],"and":[12,36,82],"kernel":[13,34,80],"functions.":[14],"The":[15,59,87],"dimension":[16],"reducing":[17],"transformation":[19],"obtained":[21,109],"by":[22,78],"implicitly":[23],"mapping":[24,41],"the":[25,50,56,74,111],"input":[26],"data":[27],"into":[28],"space":[31,52,76],"using":[32],"function,":[35],"then":[37],"finding":[38],"linear":[40],"an":[44,63,68],"orthonormal":[45,69],"basis":[46,70],"of":[47,71,96,105],"in":[49,73,110],"that":[53,91,102],"maximally":[54],"separates":[55],"between-class":[57],"relationship.":[58],"proposed":[60],"utilizes":[62],"efficient":[64],"algorithm":[65],"to":[66],"compute":[67],"transformed":[77],"function":[81],"achieves":[83],"dramatic":[84],"computational":[85],"savings.":[86],"experimental":[88],"results":[89],"demonstrate":[90],"our":[92],"capable":[95],"extracting":[97],"features":[99],"effectively":[100],"so":[101],"competitive":[103],"performance":[104],"classification":[106],"can":[107],"be":[108],"reduced":[112],"dimensional":[113],"space.":[114]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}