{"id":"https://openalex.org/W2407474579","doi":null,"title":"Optimizing locally linear classifiers with supervised anchor point learning","display_name":"Optimizing locally linear classifiers with supervised anchor point learning","publication_year":2015,"publication_date":"2015-07-25","ids":{"openalex":"https://openalex.org/W2407474579","mag":"2407474579"},"language":"en","primary_location":{"id":"mag:2407474579","doi":null,"is_oa":false,"landing_page_url":"https://ijcai.org/Proceedings/15/Papers/520.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4306419142","display_name":"International Conference on Artificial Intelligence","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":"International Conference on Artificial Intelligence","raw_type":null},"volume":null,"type":"conference-paper","is_traditional":true,"indexed_in":[],"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/A5083899881","display_name":"Xue Fei Mao","orcid":"https://orcid.org/0009-0009-7625-772X","observed_orcids":["https://orcid.org/0009-0009-7625-772X"]},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xue Mao","raw_affiliation_strings":["[NLPR, Institute of Automation, Chinese Academy of Sciences, China]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"[NLPR, Institute of Automation, Chinese Academy of Sciences, China]","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112557825","display_name":"Zhouyu Fu","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I63525965","display_name":"Western Sydney University","ror":"https://ror.org/03t52dk35","country_code":"AU","type":"education","lineage":["https://openalex.org/I63525965"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Zhouyu Fu","raw_affiliation_strings":["School of Computing, Engineering & Mathematics, University of Western Sydney, Australia#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computing, Engineering & Mathematics, University of Western Sydney, Australia#TAB#","institution_ids":["https://openalex.org/I63525965"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000753987","display_name":"Ou Wu","orcid":"https://orcid.org/0000-0002-8060-7739","observed_orcids":["https://orcid.org/0000-0002-8060-7739"]},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ou Wu","raw_affiliation_strings":["[NLPR, Institute of Automation, Chinese Academy of Sciences, China]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"[NLPR, Institute of Automation, Chinese Academy of Sciences, China]","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5114549594","display_name":"Weiming Hu","orcid":"https://orcid.org/0000-0001-9237-8825","observed_orcids":["https://orcid.org/0000-0001-9237-8825"]},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weiming Hu","raw_affiliation_strings":["[NLPR, Institute of Automation, Chinese Academy of Sciences, China]"],"raw_orcid":"https://orcid.org/0000-0001-9237-8825","affiliations":[{"raw_affiliation_string":"[NLPR, Institute of Automation, Chinese Academy of Sciences, China]","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.3586,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.48305015,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":87,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"3699","last_page":"3706"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12676","display_name":"Machine Learning and ELM","score":0.2273000031709671,"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/T12676","display_name":"Machine Learning and ELM","score":0.2273000031709671,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.17910000681877136,"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/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.16269999742507935,"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/supervised-learning","display_name":"supervised learning","score":0.6830000281333923},{"id":"https://openalex.org/keywords/nonlinear-decision-boundaries","display_name":"nonlinear decision boundaries","score":0.9160000085830688},{"id":"https://openalex.org/keywords/computational-efficiency","display_name":"computational efficiency","score":0.5609999895095825}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.7080643773078918},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6595848202705383},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6344435214996338},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6059311032295227},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5825749635696411},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5816150307655334},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5227285027503967},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.49490493535995483},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.4879402816295624},{"id":"https://openalex.org/C58973888","wikidata":"https://www.wikidata.org/wiki/Q1041418","display_name":"Semi-supervised learning","level":2,"score":0.4801849126815796},{"id":"https://openalex.org/C139532973","wikidata":"https://www.wikidata.org/wiki/Q2679259","display_name":"Linear classifier","level":3,"score":0.4696677625179291},{"id":"https://openalex.org/C106135958","wikidata":"https://www.wikidata.org/wiki/Q7291993","display_name":"Random subspace method","level":3,"score":0.4385736286640167},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.43591487407684326},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.25856781005859375},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.11598297953605652},{"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":"mag:2407474579","doi":null,"is_oa":false,"landing_page_url":"https://ijcai.org/Proceedings/15/Papers/520.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4306419142","display_name":"International Conference on Artificial Intelligence","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":"International Conference on Artificial Intelligence","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W130653142","https://openalex.org/W1497057245","https://openalex.org/W1526741802","https://openalex.org/W1540007258","https://openalex.org/W1560724230","https://openalex.org/W2099537822","https://openalex.org/W2100659887","https://openalex.org/W2107791152","https://openalex.org/W2112545207","https://openalex.org/W2112796928","https://openalex.org/W2118585731","https://openalex.org/W2123745357","https://openalex.org/W2125394697","https://openalex.org/W2125993116","https://openalex.org/W2134563198","https://openalex.org/W2137515395","https://openalex.org/W2142623206","https://openalex.org/W2145406111","https://openalex.org/W2153635508","https://openalex.org/W2165828254","https://openalex.org/W2189508540","https://openalex.org/W2543628786","https://openalex.org/W2621615146","https://openalex.org/W3120740533","https://openalex.org/W4285719527"],"related_works":["https://openalex.org/W2947060746","https://openalex.org/W2788152322","https://openalex.org/W2189508540","https://openalex.org/W7095099244","https://openalex.org/W2122167966","https://openalex.org/W2131202691","https://openalex.org/W3007705807","https://openalex.org/W2135670105","https://openalex.org/W1593641510","https://openalex.org/W7096932554"],"abstract_inverted_index":{"Kernel":[0],"SVM":[1,160],"suffers":[2],"from":[3],"high":[4],"computational":[5],"complexity":[6],"when":[7],"dealing":[8],"with":[9,28,128,157,162],"large-scale":[10],"nonlinear":[11,25],"datasets.":[12],"To":[13],"address":[14],"this":[15,96],"issue,":[16],"locally":[17,29],"linear":[18,30],"classifiers":[19,78,130],"have":[20],"been":[21],"proposed":[22],"for":[23,91,105],"approximating":[24],"decision":[26],"boundaries":[27],"functions":[31],"using":[32],"a":[33,61,100],"local":[34,55],"coding":[35,41],"scheme.":[36],"The":[37],"effectiveness":[38],"of":[39,48,63],"such":[40],"scheme":[42],"depends":[43],"heavily":[44],"on":[45,155],"the":[46,54,74,83,92,123,129,133,158],"quality":[47],"anchor":[49,65,75,85,106,117,125,149],"points":[50,76,86,126],"chosen":[51],"to":[52,131],"produce":[53],"codes.":[56],"Existing":[57],"methods":[58,145],"usually":[59],"involve":[60],"phase":[62],"unsupervised":[64,148],"point":[66,107,118,150],"learning":[67,151],"followed":[68],"by":[69],"supervised":[70,103],"classifier":[71,120],"learning.":[72,108],"Thus,":[73],"and":[77,119,152],"are":[79],"obtained":[80],"separately":[81],"whereas":[82],"learned":[84],"may":[87],"not":[88],"be":[89],"optimal":[90],"discriminative":[93],"task.":[94],"In":[95],"paper,":[97],"we":[98],"present":[99],"novel":[101],"fully":[102],"approach":[104],"A":[109],"single":[110],"optimization":[111],"problem":[112],"is":[113],"formulated":[114],"over":[115],"both":[116],"variables,":[121],"optimizing":[122],"initial":[124],"jointly":[127],"minimize":[132],"classification":[134],"risk.":[135],"Experimental":[136],"results":[137],"show":[138],"that":[139],"our":[140],"method":[141],"outperforms":[142],"other":[143],"competitive":[144],"which":[146],"employ":[147],"achieves":[153],"performance":[154],"par":[156],"kernel":[159],"albeit":[161],"much":[163],"improved":[164],"efficiency.":[165]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1}],"updated_date":"2026-10-16T09:59:22.235173","created_date":"2016-06-24T00:00:00"}
