{"id":"https://openalex.org/W2735749309","doi":"https://doi.org/10.1109/ijcnn.2017.7965875","title":"Simple, fast and accurate hyper-parameter tuning in Gaussian-kernel SVM","display_name":"Simple, fast and accurate hyper-parameter tuning in Gaussian-kernel SVM","publication_year":2017,"publication_date":"2017-05-01","ids":{"openalex":"https://openalex.org/W2735749309","doi":"https://doi.org/10.1109/ijcnn.2017.7965875","mag":"2735749309"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2017.7965875","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2017.7965875","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 International Joint Conference on Neural Networks (IJCNN)","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/A5101466169","display_name":"Guangliang Chen","orcid":"https://orcid.org/0000-0001-8334-3727"},"institutions":[{"id":"https://openalex.org/I51504820","display_name":"San Jose State University","ror":"https://ror.org/04qyvz380","country_code":"US","type":"education","lineage":["https://openalex.org/I51504820"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Guangliang Chen","raw_affiliation_strings":["Department of Mathematics & Statistics, San Jos\u00e9 State University, San Jos\u00e9, CA"],"affiliations":[{"raw_affiliation_string":"Department of Mathematics & Statistics, San Jos\u00e9 State University, San Jos\u00e9, CA","institution_ids":["https://openalex.org/I51504820"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064013271","display_name":"Wilson Florero-Salinas","orcid":null},"institutions":[{"id":"https://openalex.org/I26730717","display_name":"Foothill College","ror":"https://ror.org/00dhmq281","country_code":"US","type":"education","lineage":["https://openalex.org/I26730717"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Wilson Florero-Salinas","raw_affiliation_strings":["Mathematics Department, Foothill College, Los Altos Hills, CA"],"affiliations":[{"raw_affiliation_string":"Mathematics Department, Foothill College, Los Altos Hills, CA","institution_ids":["https://openalex.org/I26730717"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100380772","display_name":"Dan Li","orcid":"https://orcid.org/0000-0002-9161-458X"},"institutions":[{"id":"https://openalex.org/I51504820","display_name":"San Jose State University","ror":"https://ror.org/04qyvz380","country_code":"US","type":"education","lineage":["https://openalex.org/I51504820"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dan Li","raw_affiliation_strings":["Department of Mathematics & Statistics, San Jos\u00e9 State University, San Jos\u00e9, CA"],"affiliations":[{"raw_affiliation_string":"Department of Mathematics & Statistics, San Jos\u00e9 State University, San Jos\u00e9, CA","institution_ids":["https://openalex.org/I51504820"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5101466169"],"corresponding_institution_ids":["https://openalex.org/I51504820"],"apc_list":null,"apc_paid":null,"fwci":1.3651,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.85766011,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"348","last_page":"355"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.9990000128746033,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9990000128746033,"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":0.998199999332428,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.9937999844551086,"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/hyperparameter","display_name":"Hyperparameter","score":0.7876750230789185},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.644137442111969},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.5683612823486328},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5454407930374146},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5264946818351746},{"id":"https://openalex.org/keywords/gaussian-function","display_name":"Gaussian function","score":0.5202432870864868},{"id":"https://openalex.org/keywords/generalizability-theory","display_name":"Generalizability theory","score":0.5146940350532532},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.4426388442516327},{"id":"https://openalex.org/keywords/bootstrapping","display_name":"Bootstrapping (finance)","score":0.41514426469802856},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3784857988357544},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.34152525663375854},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.275570273399353},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1343178153038025}],"concepts":[{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.7876750230789185},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.644137442111969},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.5683612823486328},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5454407930374146},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5264946818351746},{"id":"https://openalex.org/C7218915","wikidata":"https://www.wikidata.org/wiki/Q1054475","display_name":"Gaussian function","level":3,"score":0.5202432870864868},{"id":"https://openalex.org/C27158222","wikidata":"https://www.wikidata.org/wiki/Q5532422","display_name":"Generalizability theory","level":2,"score":0.5146940350532532},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.4426388442516327},{"id":"https://openalex.org/C207609745","wikidata":"https://www.wikidata.org/wiki/Q4944086","display_name":"Bootstrapping (finance)","level":2,"score":0.41514426469802856},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3784857988357544},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.34152525663375854},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.275570273399353},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1343178153038025},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","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/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.2017.7965875","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2017.7965875","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320306164","display_name":"Simons Foundation","ror":"https://ror.org/01cmst727"},{"id":"https://openalex.org/F4320316409","display_name":"San Jos\u00e9 State University","ror":"https://ror.org/04qyvz380"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W182586680","https://openalex.org/W1544875853","https://openalex.org/W1629102637","https://openalex.org/W2024060531","https://openalex.org/W2037575202","https://openalex.org/W2056760934","https://openalex.org/W2087347434","https://openalex.org/W2097998348","https://openalex.org/W2099201756","https://openalex.org/W2100659887","https://openalex.org/W2109943925","https://openalex.org/W2119821739","https://openalex.org/W2124158580","https://openalex.org/W2131241448","https://openalex.org/W2139212933","https://openalex.org/W2152799677","https://openalex.org/W2153635508","https://openalex.org/W2157791002","https://openalex.org/W2165874743","https://openalex.org/W2172000360","https://openalex.org/W3004533406","https://openalex.org/W3120740533","https://openalex.org/W4239510810","https://openalex.org/W6674385629","https://openalex.org/W6678649364","https://openalex.org/W6678911119","https://openalex.org/W6682557032","https://openalex.org/W6682953061","https://openalex.org/W6684578312"],"related_works":["https://openalex.org/W2375370983","https://openalex.org/W2369557298","https://openalex.org/W2545232906","https://openalex.org/W2011212036","https://openalex.org/W3044685708","https://openalex.org/W2065131986","https://openalex.org/W1545294102","https://openalex.org/W2127643120","https://openalex.org/W4229068138","https://openalex.org/W4321262185"],"abstract_inverted_index":{"We":[0,192],"consider":[1],"the":[2,25,29,31,38,43,47,58,79,87,126,132,137,148,154,161,209],"parameter":[3,114,139],"tuning":[4],"problem":[5],"for":[6,112,136],"Gaussian-kernel":[7],"support":[8],"vector":[9],"machines,":[10],"i.e.,":[11],"how":[12],"to":[13,69,71,123,152,180,188,196,217],"set":[14,125],"its":[15,218],"two":[16],"hyperparameters":[17],"-":[18,208],"\u03c3":[19,129],"(bandwidth)":[20],"and":[21,77,93,183],"C":[22,140,150],"(tradeoff).":[23],"Among":[24],"many":[26,81],"methods":[27,73,85],"in":[28,96,220],"literature,":[30],"majority":[32],"handle":[33],"this":[34,105],"task":[35],"by":[36],"maximizing":[37],"cross":[39],"validation":[40,156,162],"accuracy":[41,163,211],"over":[42],"first":[44],"quadrant":[45],"of":[46,90,128,202,212],"(\u03c3,":[48],"C)":[49],"plane.":[50],"However,":[51],"they":[52],"are":[53],"all":[54],"computationally":[55,102],"expensive":[56],"because":[57],"objective":[59],"function":[60],"has":[61,68],"no":[62],"explicit":[63],"formula":[64],"so":[65],"that":[66,146,198],"one":[67],"resort":[70],"numerical":[72],"(which":[74],"require":[75],"training":[76,91,174],"testing":[78],"classifier":[80],"times).":[82],"Additionally,":[83],"these":[84],"ignore":[86],"intrinsic":[88],"geometry":[89],"data":[92,133],"always":[94],"operate":[95],"a":[97,109,119,200],"large":[98],"set,":[99],"thus":[100],"being":[101],"inefficient.":[103],"In":[104],"paper":[106],"we":[107,117,141],"propose":[108],"two-step":[110],"procedure":[111],"efficient":[113],"selection:":[115],"First,":[116],"use":[118],"nearest":[120],"neighbor":[121],"method":[122,145,165,214],"directly":[124],"value":[127],"based":[130],"on":[131],"geometry;":[134],"afterwards,":[135],"tradeoff":[138],"employ":[142],"an":[143],"elbow":[144],"finds":[147],"smallest":[149],"leading":[151],"\u201cnearly\u201d":[153],"highest":[155],"accuracy.":[157],"By":[158],"slightly":[159],"sacrificing":[160],"our":[164,213],"gains":[166],"additional":[167],"attractive":[168],"properties":[169],"such":[170,199],"as":[171],"(1)":[172],"faster":[173],"(i.e.,":[175],"much":[176,226],"less":[177],"candidate":[178],"points":[179],"be":[181],"examined)":[182],"(2)":[184],"better":[185],"generalizability":[186],"(due":[187],"larger":[189],"class":[190],"margins).":[191],"conduct":[193],"extensive":[194],"experiments":[195],"show":[197],"combination":[201],"simple":[203],"techniques":[204],"achieves":[205],"excellent":[206],"performance":[207],"classification":[210],"is":[215,225],"comparable":[216],"competitors":[219],"most":[221],"cases,":[222],"but":[223],"it":[224],"faster.":[227]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":1}],"updated_date":"2026-01-13T01:12:25.745995","created_date":"2025-10-10T00:00:00"}