{"id":"https://openalex.org/W2736572136","doi":"https://doi.org/10.1109/cybconf.2017.7985796","title":"Online Laplacian-Regularized Support Vector Regression","display_name":"Online Laplacian-Regularized Support Vector Regression","publication_year":2017,"publication_date":"2017-06-01","ids":{"openalex":"https://openalex.org/W2736572136","doi":"https://doi.org/10.1109/cybconf.2017.7985796","mag":"2736572136"},"language":"en","primary_location":{"id":"doi:10.1109/cybconf.2017.7985796","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cybconf.2017.7985796","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 3rd IEEE International Conference on Cybernetics (CYBCONF)","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/A5103086704","display_name":"Lianbo Zhang","orcid":"https://orcid.org/0000-0003-4509-2036"},"institutions":[{"id":"https://openalex.org/I4210162190","display_name":"China University of Petroleum, East China","ror":"https://ror.org/05gbn2817","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210162190"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Lianbo Zhang","raw_affiliation_strings":["College of Information and Control Engineering, China University of Petroleum (East China), Qingdao, Shandong, China"],"affiliations":[{"raw_affiliation_string":"College of Information and Control Engineering, China University of Petroleum (East China), Qingdao, Shandong, China","institution_ids":["https://openalex.org/I4210162190"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100444156","display_name":"Weifeng Liu","orcid":"https://orcid.org/0000-0002-5388-9080"},"institutions":[{"id":"https://openalex.org/I4210162190","display_name":"China University of Petroleum, East China","ror":"https://ror.org/05gbn2817","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210162190"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weifeng Liu","raw_affiliation_strings":["College of Information and Control Engineering, China University of Petroleum (East China), Qingdao, Shandong, China"],"affiliations":[{"raw_affiliation_string":"College of Information and Control Engineering, China University of Petroleum (East China), Qingdao, Shandong, China","institution_ids":["https://openalex.org/I4210162190"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5103086704"],"corresponding_institution_ids":["https://openalex.org/I4210162190"],"apc_list":null,"apc_paid":null,"fwci":0.182,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.55932039,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"7","issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9976000189781189,"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":0.9976000189781189,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9905999898910522,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.989799976348877,"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/computer-science","display_name":"Computer science","score":0.7379884719848633},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.7170113325119019},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.7142307162284851},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5848244428634644},{"id":"https://openalex.org/keywords/online-learning","display_name":"Online learning","score":0.519096851348877},{"id":"https://openalex.org/keywords/laplace-operator","display_name":"Laplace operator","score":0.5159916877746582},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.47938111424446106},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.44164854288101196},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.428615003824234},{"id":"https://openalex.org/keywords/online-algorithm","display_name":"Online algorithm","score":0.4191287159919739},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.4176397919654846},{"id":"https://openalex.org/keywords/manifold-alignment","display_name":"Manifold alignment","score":0.41258493065834045},{"id":"https://openalex.org/keywords/nonlinear-dimensionality-reduction","display_name":"Nonlinear dimensionality reduction","score":0.4063810706138611},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.38034507632255554},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.27532875537872314},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.15066096186637878},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1410444974899292},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.08278438448905945}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7379884719848633},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.7170113325119019},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.7142307162284851},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5848244428634644},{"id":"https://openalex.org/C2986087404","wikidata":"https://www.wikidata.org/wiki/Q15946010","display_name":"Online learning","level":2,"score":0.519096851348877},{"id":"https://openalex.org/C165700671","wikidata":"https://www.wikidata.org/wiki/Q203484","display_name":"Laplace operator","level":2,"score":0.5159916877746582},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47938111424446106},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.44164854288101196},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.428615003824234},{"id":"https://openalex.org/C196921405","wikidata":"https://www.wikidata.org/wiki/Q786431","display_name":"Online algorithm","level":2,"score":0.4191287159919739},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.4176397919654846},{"id":"https://openalex.org/C153120616","wikidata":"https://www.wikidata.org/wiki/Q17068315","display_name":"Manifold alignment","level":4,"score":0.41258493065834045},{"id":"https://openalex.org/C151876577","wikidata":"https://www.wikidata.org/wiki/Q7049464","display_name":"Nonlinear dimensionality reduction","level":3,"score":0.4063810706138611},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.38034507632255554},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.27532875537872314},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.15066096186637878},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1410444974899292},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.08278438448905945},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cybconf.2017.7985796","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cybconf.2017.7985796","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 3rd IEEE International Conference on Cybernetics (CYBCONF)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.5799999833106995,"id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W573892002","https://openalex.org/W1479807131","https://openalex.org/W1603138887","https://openalex.org/W1664825283","https://openalex.org/W1695396496","https://openalex.org/W1964357740","https://openalex.org/W1972084483","https://openalex.org/W1977073705","https://openalex.org/W2002055708","https://openalex.org/W2012852250","https://openalex.org/W2018729757","https://openalex.org/W2029307344","https://openalex.org/W2033855314","https://openalex.org/W2076063813","https://openalex.org/W2083003257","https://openalex.org/W2083670761","https://openalex.org/W2091642480","https://openalex.org/W2104290444","https://openalex.org/W2133218851","https://openalex.org/W2141840626","https://openalex.org/W2148825261","https://openalex.org/W2150621701","https://openalex.org/W2152756885","https://openalex.org/W2160218441","https://openalex.org/W2997701990","https://openalex.org/W3009009611","https://openalex.org/W3018189936","https://openalex.org/W3098527277","https://openalex.org/W3120740533","https://openalex.org/W4292022450","https://openalex.org/W6637179743","https://openalex.org/W6675747103","https://openalex.org/W6681723013","https://openalex.org/W6683584131"],"related_works":["https://openalex.org/W3109610583","https://openalex.org/W2387045723","https://openalex.org/W2375518579","https://openalex.org/W117517268","https://openalex.org/W2944373987","https://openalex.org/W65619410","https://openalex.org/W2112684860","https://openalex.org/W2391701611","https://openalex.org/W2149544245","https://openalex.org/W2109380943"],"abstract_inverted_index":{"In":[0,130],"recent":[1],"years,":[2],"with":[3,180],"the":[4,10,13,75,113,116,126,163,169,192],"growing":[5],"quantity":[6],"of":[7,15,42,77,98,115,172,182],"data":[8,117,181],"and":[9,82,167,195],"explosion":[11],"in":[12,144],"amount":[14],"available":[16],"information,":[17],"much":[18],"effort":[19],"has":[20,71,103],"been":[21,72,104],"devoted":[22],"by":[23],"researchers":[24],"to":[25,30,85,92,111,124,205],"develop":[26],"better":[27,207],"learning":[28,38,49,68,108],"methods":[29,44],"address":[31],"these":[32,35],"issues.":[33],"Among":[34],"methods,":[36,174],"online":[37,59,67,127,137,142,152,158,210],"is":[39,64,83,189,203],"one":[40,53],"set":[41],"instrumental":[43],"that":[45,70,106,139,198,200],"could":[46],"fit":[47],"such":[48],"scenarios":[50],"through":[51],"training":[52],"example":[54],"at":[55],"a":[56,65,95,122,135,145],"time.":[57],"Specifically,":[58],"support":[60,78],"vector":[61,79],"regression":[62],"(SVR)":[63],"typical":[66],"method":[69,138],"developed":[73],"on":[74],"basis":[76],"machines":[80],"(SVM)":[81],"able":[84,204],"achieve":[86],"effective":[87],"performance.":[88],"However,":[89],"it":[90,102,120],"fails":[91],"adequately":[93],"utilize":[94],"large":[96],"mass":[97],"unlabelled":[99],"data.":[100],"Meanwhile,":[101],"shown":[105],"manifold":[107,128,146],"enables":[109],"us":[110],"exploit":[112],"geometry":[114],"distribution,":[118],"but":[119],"remains":[121],"challenge":[123],"explore":[125],"process.":[129],"this":[131],"paper,":[132],"we":[133,150],"propose":[134],"new":[136],"incorporates":[140],"standard":[141,209],"SVR":[143,154,211],"regularized":[147],"framework,":[148],"which":[149,175],"call":[151],"Laplacian-regularized":[153],"(online":[155],"LapSVR).":[156],"Our":[157],"LapSVR":[159],"algorithm":[160,202],"can":[161],"tackle":[162],"problems":[164],"described":[165],"above":[166],"avoid":[168],"repeated":[170],"calculations":[171],"batch":[173],"require":[176],"intensive":[177],"computation,":[178],"especially":[179],"massive":[183],"size":[184],"or":[185],"dimensions.":[186],"Experimental":[187],"evidence":[188],"presented":[190],"for":[191],"Housing,":[193],"Auto-MPG":[194],"DEAP":[196],"datasets":[197],"suggests":[199],"our":[201],"perform":[206],"than":[208],"methods.":[212]},"counts_by_year":[{"year":2020,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
