{"id":"https://openalex.org/W4391409194","doi":"https://doi.org/10.1109/wsc60868.2023.10407300","title":"Efficient Bandwidth Selection for Kernel Density Estimation","display_name":"Efficient Bandwidth Selection for Kernel Density Estimation","publication_year":2023,"publication_date":"2023-12-10","ids":{"openalex":"https://openalex.org/W4391409194","doi":"https://doi.org/10.1109/wsc60868.2023.10407300"},"language":"en","primary_location":{"id":"doi:10.1109/wsc60868.2023.10407300","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/wsc60868.2023.10407300","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 Winter Simulation Conference (WSC)","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/A5100633220","display_name":"Haidong Li","orcid":"https://orcid.org/0000-0001-9939-7164"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haidong Li","raw_affiliation_strings":["University of Chinese Academy of Sciences,Department of Management Science,Beijing,China,100190"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Chinese Academy of Sciences,Department of Management Science,Beijing,China,100190","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100447536","display_name":"Long Wang","orcid":"https://orcid.org/0000-0001-5600-8157"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Long Wang","raw_affiliation_strings":["Peking University,Department of Advanced Manufacturing and Robotics,Beijing,China,100871"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Peking University,Department of Advanced Manufacturing and Robotics,Beijing,China,100871","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005503619","display_name":"Yijie Peng","orcid":"https://orcid.org/0000-0003-2584-8131"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yijie Peng","raw_affiliation_strings":["Peking University,Department of Management Science and Information Systems,Beijing,China,100871"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Peking University,Department of Management Science and Information Systems,Beijing,China,100871","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100401463","display_name":"Di Wang","orcid":"https://orcid.org/0000-0003-0435-0609"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Di Wang","raw_affiliation_strings":["Shanghai Jiao Tong University,Department of Industrial Engineering and Management,Shanghai,China,200240"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University,Department of Industrial Engineering and Management,Shanghai,China,200240","institution_ids":["https://openalex.org/I183067930"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.3442,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.6129919,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":"9","issue":null,"first_page":"552","last_page":"563"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11236","display_name":"Control Systems and Identification","score":0.9940000176429749,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"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/T11236","display_name":"Control Systems and Identification","score":0.9940000176429749,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"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/T10901","display_name":"Advanced Data Compression Techniques","score":0.98580002784729,"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/T10136","display_name":"Statistical Methods and Inference","score":0.9787999987602234,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/kernel-density-estimation","display_name":"Kernel density estimation","score":0.7668542265892029},{"id":"https://openalex.org/keywords/bandwidth","display_name":"Bandwidth (computing)","score":0.7337606549263},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.7148841023445129},{"id":"https://openalex.org/keywords/variable-kernel-density-estimation","display_name":"Variable kernel density estimation","score":0.6656067371368408},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.5277419686317444},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.48870161175727844},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3897801637649536},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.38898766040802},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3564620018005371},{"id":"https://openalex.org/keywords/kernel-method","display_name":"Kernel method","score":0.3553099036216736},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.2164747714996338},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.17024394869804382},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.0665183961391449},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.06431609392166138}],"concepts":[{"id":"https://openalex.org/C71134354","wikidata":"https://www.wikidata.org/wiki/Q458825","display_name":"Kernel density estimation","level":3,"score":0.7668542265892029},{"id":"https://openalex.org/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.7337606549263},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.7148841023445129},{"id":"https://openalex.org/C195699287","wikidata":"https://www.wikidata.org/wiki/Q7915722","display_name":"Variable kernel density estimation","level":4,"score":0.6656067371368408},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.5277419686317444},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.48870161175727844},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3897801637649536},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.38898766040802},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3564620018005371},{"id":"https://openalex.org/C122280245","wikidata":"https://www.wikidata.org/wiki/Q620622","display_name":"Kernel method","level":3,"score":0.3553099036216736},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.2164747714996338},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.17024394869804382},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.0665183961391449},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.06431609392166138},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/wsc60868.2023.10407300","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/wsc60868.2023.10407300","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 Winter Simulation Conference (WSC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W79918814","https://openalex.org/W1489950266","https://openalex.org/W1511694993","https://openalex.org/W1984499217","https://openalex.org/W1998378660","https://openalex.org/W2004840619","https://openalex.org/W2057218616","https://openalex.org/W2070084003","https://openalex.org/W2094771755","https://openalex.org/W2104827669","https://openalex.org/W2108447811","https://openalex.org/W2137276647","https://openalex.org/W3066422803","https://openalex.org/W4212774754","https://openalex.org/W4235667863","https://openalex.org/W4248721357","https://openalex.org/W4254307951","https://openalex.org/W4295111190","https://openalex.org/W4295134715","https://openalex.org/W6603230449","https://openalex.org/W6741833390","https://openalex.org/W6786425933"],"related_works":["https://openalex.org/W2127229869","https://openalex.org/W1603091392","https://openalex.org/W2004333127","https://openalex.org/W2420851703","https://openalex.org/W3123056048","https://openalex.org/W4389251307","https://openalex.org/W2165576085","https://openalex.org/W4386075310","https://openalex.org/W2079825755","https://openalex.org/W2179275589"],"abstract_inverted_index":{"We":[0],"consider":[1],"bandwidth":[2,37],"selection":[3],"for":[4],"kernel":[5,11,30,47,63],"density":[6,12,31,48],"estimation.":[7],"The":[8,55],"performance":[9,84],"of":[10,19,62,87],"estimator":[13,32,49],"heavily":[14],"relies":[15],"on":[16],"the":[17,20,36,40,51,59,88],"quality":[18],"bandwidth.":[21,54],"In":[22],"this":[23],"paper,":[24],"we":[25],"propose":[26],"an":[27],"efficient":[28],"plug-in":[29,73],"which":[33],"first":[34],"perturbs":[35],"to":[38],"estimate":[39],"optimal":[41,53],"bandwidth,":[42],"followed":[43],"by":[44],"applying":[45],"a":[46,67],"with":[50],"estimated":[52],"proposed":[56,89],"method":[57],"utilizes":[58],"zeroth-order":[60],"information":[61],"function":[64],"and":[65,85],"has":[66],"faster":[68],"convergence":[69],"rate":[70],"than":[71],"other":[72],"methods":[74],"in":[75],"existing":[76],"literature.":[77],"Simulation":[78],"results":[79],"demonstrate":[80],"superior":[81],"finite":[82],"sample":[83],"robustness":[86],"method.":[90]},"counts_by_year":[{"year":2024,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}