{"id":"https://openalex.org/W2143243940","doi":"https://doi.org/10.1109/icassp.2009.4959899","title":"Space Kernel Analysis","display_name":"Space Kernel Analysis","publication_year":2009,"publication_date":"2009-04-01","ids":{"openalex":"https://openalex.org/W2143243940","doi":"https://doi.org/10.1109/icassp.2009.4959899","mag":"2143243940"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2009.4959899","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2009.4959899","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 IEEE International Conference on Acoustics, Speech and Signal Processing","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/A5018983486","display_name":"Liuling Gong","orcid":null},"institutions":[{"id":"https://openalex.org/I39422238","display_name":"University of Illinois Chicago","ror":"https://ror.org/02mpq6x41","country_code":"US","type":"education","lineage":["https://openalex.org/I39422238"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Liuling Gong","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Illinois, Chicago, Chicago, IL, USA","University of Illinois at Chicago, Dept. of Electrical and Computer Engineering, 851 S Morgan St, 60607, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Illinois, Chicago, Chicago, IL, USA","institution_ids":["https://openalex.org/I39422238"]},{"raw_affiliation_string":"University of Illinois at Chicago, Dept. of Electrical and Computer Engineering, 851 S Morgan St, 60607, USA","institution_ids":["https://openalex.org/I39422238"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5081723612","display_name":"Dan Schonfeld","orcid":"https://orcid.org/0000-0002-2772-4821"},"institutions":[{"id":"https://openalex.org/I39422238","display_name":"University of Illinois Chicago","ror":"https://ror.org/02mpq6x41","country_code":"US","type":"education","lineage":["https://openalex.org/I39422238"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dan Schonfeld","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Illinois, Chicago, Chicago, IL, USA","University of Illinois at Chicago, Dept. of Electrical and Computer Engineering, 851 S Morgan St, 60607, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Illinois, Chicago, Chicago, IL, USA","institution_ids":["https://openalex.org/I39422238"]},{"raw_affiliation_string":"University of Illinois at Chicago, Dept. of Electrical and Computer Engineering, 851 S Morgan St, 60607, USA","institution_ids":["https://openalex.org/I39422238"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.9059,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.81850433,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1577","last_page":"1580"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9991999864578247,"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"}},"topics":[{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9991999864578247,"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/T10057","display_name":"Face and Expression Recognition","score":0.9915000200271606,"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/T14257","display_name":"Advanced Measurement and Detection Methods","score":0.9642000198364258,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/kernel-embedding-of-distributions","display_name":"Kernel embedding of distributions","score":0.7208945155143738},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.6721763610839844},{"id":"https://openalex.org/keywords/kernel-principal-component-analysis","display_name":"Kernel principal component analysis","score":0.6592974066734314},{"id":"https://openalex.org/keywords/variable-kernel-density-estimation","display_name":"Variable kernel density estimation","score":0.6541535258293152},{"id":"https://openalex.org/keywords/radial-basis-function-kernel","display_name":"Radial basis function kernel","score":0.6189380884170532},{"id":"https://openalex.org/keywords/polynomial-kernel","display_name":"Polynomial kernel","score":0.5289492607116699},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.48317256569862366},{"id":"https://openalex.org/keywords/kernel-method","display_name":"Kernel method","score":0.47769930958747864},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.430133581161499},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.4298549294471741},{"id":"https://openalex.org/keywords/nonparametric-statistics","display_name":"Nonparametric statistics","score":0.4169533848762512},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4114637076854706},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.39045247435569763},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1742333471775055},{"id":"https://openalex.org/keywords/discrete-mathematics","display_name":"Discrete mathematics","score":0.09636616706848145},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.08499389886856079}],"concepts":[{"id":"https://openalex.org/C134517425","wikidata":"https://www.wikidata.org/wiki/Q16000131","display_name":"Kernel embedding of distributions","level":4,"score":0.7208945155143738},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.6721763610839844},{"id":"https://openalex.org/C182335926","wikidata":"https://www.wikidata.org/wiki/Q17093020","display_name":"Kernel principal component analysis","level":4,"score":0.6592974066734314},{"id":"https://openalex.org/C195699287","wikidata":"https://www.wikidata.org/wiki/Q7915722","display_name":"Variable kernel density estimation","level":4,"score":0.6541535258293152},{"id":"https://openalex.org/C75866337","wikidata":"https://www.wikidata.org/wiki/Q7280263","display_name":"Radial basis function kernel","level":4,"score":0.6189380884170532},{"id":"https://openalex.org/C160446489","wikidata":"https://www.wikidata.org/wiki/Q7226642","display_name":"Polynomial kernel","level":4,"score":0.5289492607116699},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.48317256569862366},{"id":"https://openalex.org/C122280245","wikidata":"https://www.wikidata.org/wiki/Q620622","display_name":"Kernel method","level":3,"score":0.47769930958747864},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.430133581161499},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.4298549294471741},{"id":"https://openalex.org/C102366305","wikidata":"https://www.wikidata.org/wiki/Q1097688","display_name":"Nonparametric statistics","level":2,"score":0.4169533848762512},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4114637076854706},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.39045247435569763},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1742333471775055},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.09636616706848145},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.08499389886856079},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"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/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/icassp.2009.4959899","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2009.4959899","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 IEEE International Conference on Acoustics, Speech and Signal Processing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W362013703","https://openalex.org/W1567052132","https://openalex.org/W1823583751","https://openalex.org/W2024983310","https://openalex.org/W2062424141","https://openalex.org/W2076118331","https://openalex.org/W2103116581","https://openalex.org/W2148603752","https://openalex.org/W2149723649","https://openalex.org/W2480642495","https://openalex.org/W2802922458","https://openalex.org/W4237171445","https://openalex.org/W6638787444"],"related_works":["https://openalex.org/W2393746448","https://openalex.org/W1984421104","https://openalex.org/W2071590642","https://openalex.org/W2384322977","https://openalex.org/W2512565647","https://openalex.org/W2366185040","https://openalex.org/W2127229869","https://openalex.org/W2027376491","https://openalex.org/W1636580594","https://openalex.org/W2164869055"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3,42],"propose":[4],"a":[5,16,46],"novel":[6],"nonparametric":[7,109],"modeling":[8,110],"technique,":[9],"namely":[10],"Space":[11],"Kernel":[12,119],"Analysis":[13],"(SKA),":[14],"as":[15],"result":[17],"of":[18,21,29,49,74,135],"the":[19,22,27,38,50,60,84,98,117],"definition":[20],"space":[23,51,99,139],"kernel.":[24],"We":[25],"analyze":[26],"uncertainty":[28],"SKA":[30,34,54,75,82,105,136],"and":[31,62,64,78,95,106,128],"show":[32],"that":[33,81,116],"is":[35,55,76,93],"subjected":[36],"to":[37,57],"bias/variance":[39],"dilemma.":[40],"Nevertheless,":[41],"demonstrate":[43],"that,":[44],"by":[45,97],"proper":[47],"choice":[48],"kernel":[52,100,140],"matrix,":[53],"able":[56],"balance":[58],"between":[59,104],"robustness":[61],"accuracy":[63],"hence":[65],"outperforms":[66],"other":[67,108],"kernel-based":[68],"learning":[69],"methods.":[70],"The":[71,102],"cost":[72,88],"function":[73,89],"derived,":[77],"it":[79],"proves":[80],"minimizes":[83],"Weighted":[85],"Least":[86],"Squared":[87],"whose":[90],"weight":[91],"matrix":[92],"diagonal":[94],"determined":[96],"matrix.":[101],"parallels":[103],"several":[107],"techniques":[111],"are":[112,133],"examined.":[113],"Study":[114],"shows":[115],"traditional":[118],"Regression,":[120],"General":[121],"Regression":[122],"Neural":[123],"Network,":[124],"Similarity":[125],"Based":[126],"Modeling":[127],"Radial":[129],"Basis":[130],"Function":[131],"Network":[132],"examples":[134],"with":[137],"specified":[138],"matrices.":[141]},"counts_by_year":[{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":1},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":2},{"year":2012,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
