{"id":"https://openalex.org/W2135833316","doi":"https://doi.org/10.1109/ijcnn.2008.4634306","title":"Sparse kernel models for spectral clustering using the incomplete Cholesky decomposition","display_name":"Sparse kernel models for spectral clustering using the incomplete Cholesky decomposition","publication_year":2008,"publication_date":"2008-06-01","ids":{"openalex":"https://openalex.org/W2135833316","doi":"https://doi.org/10.1109/ijcnn.2008.4634306","mag":"2135833316"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2008.4634306","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2008.4634306","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence)","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/A5049697384","display_name":"Carlos Alzate","orcid":"https://orcid.org/0000-0003-2434-2534"},"institutions":[{"id":"https://openalex.org/I99464096","display_name":"KU Leuven","ror":"https://ror.org/05f950310","country_code":"BE","type":"education","lineage":["https://openalex.org/I99464096"]}],"countries":["BE"],"is_corresponding":true,"raw_author_name":"Carlos Alzate","raw_affiliation_strings":["Department of Electrical Engineering ESATSCD-SISTA, Katholieke Universiteit Leuven, Leuven, Belgium","Dept. of Electr. Eng. ESATSCD-SISTA, Katholieke Univ. Leuven, Leuven"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering ESATSCD-SISTA, Katholieke Universiteit Leuven, Leuven, Belgium","institution_ids":["https://openalex.org/I99464096"]},{"raw_affiliation_string":"Dept. of Electr. Eng. ESATSCD-SISTA, Katholieke Univ. Leuven, Leuven","institution_ids":["https://openalex.org/I99464096"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5078854904","display_name":"Johan A. K. Suykens","orcid":"https://orcid.org/0000-0002-8846-6352"},"institutions":[{"id":"https://openalex.org/I99464096","display_name":"KU Leuven","ror":"https://ror.org/05f950310","country_code":"BE","type":"education","lineage":["https://openalex.org/I99464096"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Johan A. K. Suykens","raw_affiliation_strings":["Department of Electrical Engineering ESATSCD-SISTA, Katholieke Universiteit Leuven, Leuven, Belgium","Dept. of Electr. Eng. ESATSCD-SISTA, Katholieke Univ. Leuven, Leuven"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering ESATSCD-SISTA, Katholieke Universiteit Leuven, Leuven, Belgium","institution_ids":["https://openalex.org/I99464096"]},{"raw_affiliation_string":"Dept. of Electr. Eng. ESATSCD-SISTA, Katholieke Univ. Leuven, Leuven","institution_ids":["https://openalex.org/I99464096"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5049697384"],"corresponding_institution_ids":["https://openalex.org/I99464096"],"apc_list":null,"apc_paid":null,"fwci":2.9933,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":{"value":0.9133197,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":"25","issue":null,"first_page":"3556","last_page":"3563"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9969000220298767,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9969000220298767,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9846000075340271,"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":0.9828000068664551,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/cholesky-decomposition","display_name":"Cholesky decomposition","score":0.9271950721740723},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6810998916625977},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.6133580207824707},{"id":"https://openalex.org/keywords/minimum-degree-algorithm","display_name":"Minimum degree algorithm","score":0.6073600649833679},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5190985202789307},{"id":"https://openalex.org/keywords/spectral-clustering","display_name":"Spectral clustering","score":0.4852166473865509},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4553024470806122},{"id":"https://openalex.org/keywords/kernel-principal-component-analysis","display_name":"Kernel principal component analysis","score":0.4314005374908447},{"id":"https://openalex.org/keywords/kernel-method","display_name":"Kernel method","score":0.418739378452301},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3995613157749176},{"id":"https://openalex.org/keywords/incomplete-cholesky-factorization","display_name":"Incomplete Cholesky factorization","score":0.3969741463661194},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.35117828845977783},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2815966010093689},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.07539361715316772}],"concepts":[{"id":"https://openalex.org/C34727166","wikidata":"https://www.wikidata.org/wiki/Q515375","display_name":"Cholesky decomposition","level":3,"score":0.9271950721740723},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6810998916625977},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.6133580207824707},{"id":"https://openalex.org/C46085209","wikidata":"https://www.wikidata.org/wiki/Q17098969","display_name":"Minimum degree algorithm","level":5,"score":0.6073600649833679},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5190985202789307},{"id":"https://openalex.org/C105611402","wikidata":"https://www.wikidata.org/wiki/Q2976589","display_name":"Spectral clustering","level":3,"score":0.4852166473865509},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4553024470806122},{"id":"https://openalex.org/C182335926","wikidata":"https://www.wikidata.org/wiki/Q17093020","display_name":"Kernel principal component analysis","level":4,"score":0.4314005374908447},{"id":"https://openalex.org/C122280245","wikidata":"https://www.wikidata.org/wiki/Q620622","display_name":"Kernel method","level":3,"score":0.418739378452301},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3995613157749176},{"id":"https://openalex.org/C44363057","wikidata":"https://www.wikidata.org/wiki/Q6015160","display_name":"Incomplete Cholesky factorization","level":4,"score":0.3969741463661194},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.35117828845977783},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2815966010093689},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.07539361715316772},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.0},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn.2008.4634306","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2008.4634306","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":45,"referenced_works":["https://openalex.org/W26816478","https://openalex.org/W200434350","https://openalex.org/W1496317909","https://openalex.org/W1578099820","https://openalex.org/W1588424744","https://openalex.org/W1676820704","https://openalex.org/W1975172027","https://openalex.org/W2017275917","https://openalex.org/W2065371646","https://openalex.org/W2069840066","https://openalex.org/W2088032561","https://openalex.org/W2094435468","https://openalex.org/W2099242680","https://openalex.org/W2105681109","https://openalex.org/W2107940287","https://openalex.org/W2121927366","https://openalex.org/W2121947440","https://openalex.org/W2125531986","https://openalex.org/W2129116669","https://openalex.org/W2137557016","https://openalex.org/W2141465109","https://openalex.org/W2145544165","https://openalex.org/W2152322845","https://openalex.org/W2153934661","https://openalex.org/W2155754954","https://openalex.org/W2159935273","https://openalex.org/W2165874743","https://openalex.org/W2166751192","https://openalex.org/W2610857016","https://openalex.org/W2798909945","https://openalex.org/W2950388929","https://openalex.org/W4235169531","https://openalex.org/W4241822132","https://openalex.org/W4285719527","https://openalex.org/W4301501800","https://openalex.org/W6601080436","https://openalex.org/W6608197349","https://openalex.org/W6634941687","https://openalex.org/W6637266410","https://openalex.org/W6679489070","https://openalex.org/W6680634009","https://openalex.org/W6680735885","https://openalex.org/W6681474176","https://openalex.org/W6683047094","https://openalex.org/W6684578312"],"related_works":["https://openalex.org/W2039814159","https://openalex.org/W898189783","https://openalex.org/W2049943687","https://openalex.org/W2381435995","https://openalex.org/W2104481679","https://openalex.org/W2041033288","https://openalex.org/W2028693659","https://openalex.org/W3046276560","https://openalex.org/W2053627399","https://openalex.org/W2079508979"],"abstract_inverted_index":{"A":[0,92],"new":[1],"sparse":[2],"kernel":[3,36],"model":[4,57,62],"for":[5,105],"spectral":[6,27,43],"clustering":[7,28,61],"is":[8,12,47,73,96],"presented.":[9],"This":[10],"method":[11,95],"based":[13],"on":[14],"the":[15,60,86,102],"incomplete":[16,70],"Cholesky":[17,71],"decomposition":[18,72],"and":[19,55,114],"can":[20],"be":[21,64],"used":[22,74],"to":[23,63,66,75,99],"efficiently":[24,101],"solve":[25],"large-scale":[26,111],"problems.":[29],"The":[30,45,69],"formulation":[31],"arises":[32],"from":[33,85],"a":[34,49,80],"weighted":[35],"principal":[37],"component":[38],"analysis":[39],"(PCA)":[40],"interpretation":[41,46],"of":[42,79,121],"clustering.":[44],"within":[48],"constrained":[50],"optimization":[51],"framework":[52],"with":[53,110],"primal":[54],"dual":[56],"representations":[58],"allowing":[59],"extended":[65],"out-of-sample":[67,106],"points.":[68],"compute":[76,100],"low-rank":[77],"approximations":[78],"modified":[81],"affinity":[82],"matrix":[83],"derived":[84],"data":[87],"which":[88],"contains":[89],"cluster":[90,103],"information.":[91],"reduced":[93],"set":[94],"also":[97],"presented":[98],"indicators":[104],"data.":[107],"Simulation":[108],"results":[109],"toy":[112],"datasets":[113],"images":[115],"show":[116],"improved":[117],"performance":[118],"in":[119],"terms":[120],"computational":[122],"complexity.":[123]},"counts_by_year":[{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":3},{"year":2015,"cited_by_count":4},{"year":2014,"cited_by_count":2},{"year":2012,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}