{"id":"https://openalex.org/W2015442739","doi":"https://doi.org/10.1109/icmlc.2010.5581058","title":"Learning large margin nearest neighbor classifiers via cutting plane algorithm","display_name":"Learning large margin nearest neighbor classifiers via cutting plane algorithm","publication_year":2010,"publication_date":"2010-07-01","ids":{"openalex":"https://openalex.org/W2015442739","doi":"https://doi.org/10.1109/icmlc.2010.5581058","mag":"2015442739"},"language":"en","primary_location":{"id":"doi:10.1109/icmlc.2010.5581058","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmlc.2010.5581058","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 International Conference on Machine Learning and Cybernetics","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/A5068389379","display_name":"Xiangyun Qing","orcid":"https://orcid.org/0000-0003-3874-0728"},"institutions":[{"id":"https://openalex.org/I143593769","display_name":"East China University of Science and Technology","ror":"https://ror.org/01vyrm377","country_code":"CN","type":"education","lineage":["https://openalex.org/I143593769"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiang-Yun Qing","raw_affiliation_strings":["School of Information Science and Engineering, East China University of Science and Technology, Shanghai, China","School of Information Science & Engineering, East China University of Science & Technology, Shanghai 200237, China#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Science and Engineering, East China University of Science and Technology, Shanghai, China","institution_ids":["https://openalex.org/I143593769"]},{"raw_affiliation_string":"School of Information Science & Engineering, East China University of Science & Technology, Shanghai 200237, China#TAB#","institution_ids":["https://openalex.org/I143593769"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100670255","display_name":"Peng Ding","orcid":"https://orcid.org/0000-0003-4419-4858"},"institutions":[{"id":"https://openalex.org/I143593769","display_name":"East China University of Science and Technology","ror":"https://ror.org/01vyrm377","country_code":"CN","type":"education","lineage":["https://openalex.org/I143593769"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Peng Ding","raw_affiliation_strings":["School of Information Science and Engineering, East China University of Science and Technology, Shanghai, China","School of Information Science & Engineering, East China University of Science & Technology, Shanghai 200237, China#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Science and Engineering, East China University of Science and Technology, Shanghai, China","institution_ids":["https://openalex.org/I143593769"]},{"raw_affiliation_string":"School of Information Science & Engineering, East China University of Science & Technology, Shanghai 200237, China#TAB#","institution_ids":["https://openalex.org/I143593769"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100351264","display_name":"Xingyu Wang","orcid":"https://orcid.org/0000-0002-0897-9933"},"institutions":[{"id":"https://openalex.org/I143593769","display_name":"East China University of Science and Technology","ror":"https://ror.org/01vyrm377","country_code":"CN","type":"education","lineage":["https://openalex.org/I143593769"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xing-Yu Wang","raw_affiliation_strings":["School of Information Science and Engineering, East China University of Science and Technology, Shanghai, China","School of Information Science & Engineering, East China University of Science & Technology, Shanghai 200237, China#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Science and Engineering, East China University of Science and Technology, Shanghai, China","institution_ids":["https://openalex.org/I143593769"]},{"raw_affiliation_string":"School of Information Science & Engineering, East China University of Science & Technology, Shanghai 200237, China#TAB#","institution_ids":["https://openalex.org/I143593769"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I143593769"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.10183066,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"10","issue":null,"first_page":"241","last_page":"246"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9987000226974487,"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":0.9987000226974487,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9921000003814697,"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9883999824523926,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/large-margin-nearest-neighbor","display_name":"Large margin nearest neighbor","score":0.9207223057746887},{"id":"https://openalex.org/keywords/mahalanobis-distance","display_name":"Mahalanobis distance","score":0.7909442186355591},{"id":"https://openalex.org/keywords/k-nearest-neighbors-algorithm","display_name":"k-nearest neighbors algorithm","score":0.774008572101593},{"id":"https://openalex.org/keywords/maxima-and-minima","display_name":"Maxima and minima","score":0.6858742833137512},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.6110121011734009},{"id":"https://openalex.org/keywords/nearest-neighbor-search","display_name":"Nearest neighbor search","score":0.6002411842346191},{"id":"https://openalex.org/keywords/semidefinite-programming","display_name":"Semidefinite programming","score":0.560869574546814},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5582286715507507},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.5424796342849731},{"id":"https://openalex.org/keywords/nearest-neighbor-graph","display_name":"Nearest neighbor graph","score":0.5226823687553406},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5116815567016602},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.49752238392829895},{"id":"https://openalex.org/keywords/cutting-plane-method","display_name":"Cutting-plane method","score":0.47340378165245056},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.46542924642562866},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.4394884407520294},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.30666473507881165},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.24496135115623474},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.2011922299861908}],"concepts":[{"id":"https://openalex.org/C94475309","wikidata":"https://www.wikidata.org/wiki/Q6489154","display_name":"Large margin nearest neighbor","level":3,"score":0.9207223057746887},{"id":"https://openalex.org/C1921717","wikidata":"https://www.wikidata.org/wiki/Q1334846","display_name":"Mahalanobis distance","level":2,"score":0.7909442186355591},{"id":"https://openalex.org/C113238511","wikidata":"https://www.wikidata.org/wiki/Q1071612","display_name":"k-nearest neighbors algorithm","level":2,"score":0.774008572101593},{"id":"https://openalex.org/C186633575","wikidata":"https://www.wikidata.org/wiki/Q845060","display_name":"Maxima and minima","level":2,"score":0.6858742833137512},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.6110121011734009},{"id":"https://openalex.org/C116738811","wikidata":"https://www.wikidata.org/wiki/Q608751","display_name":"Nearest neighbor search","level":2,"score":0.6002411842346191},{"id":"https://openalex.org/C101901036","wikidata":"https://www.wikidata.org/wiki/Q2269096","display_name":"Semidefinite programming","level":2,"score":0.560869574546814},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5582286715507507},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.5424796342849731},{"id":"https://openalex.org/C90988772","wikidata":"https://www.wikidata.org/wiki/Q2855103","display_name":"Nearest neighbor graph","level":3,"score":0.5226823687553406},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5116815567016602},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.49752238392829895},{"id":"https://openalex.org/C109839438","wikidata":"https://www.wikidata.org/wiki/Q1762039","display_name":"Cutting-plane method","level":3,"score":0.47340378165245056},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.46542924642562866},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.4394884407520294},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.30666473507881165},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.24496135115623474},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.2011922299861908},{"id":"https://openalex.org/C56086750","wikidata":"https://www.wikidata.org/wiki/Q6042592","display_name":"Integer programming","level":2,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icmlc.2010.5581058","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmlc.2010.5581058","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 International Conference on Machine Learning and Cybernetics","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1581558595","https://openalex.org/W1989617207","https://openalex.org/W2005688170","https://openalex.org/W2014987111","https://openalex.org/W2084812512","https://openalex.org/W2088779313","https://openalex.org/W2095979710","https://openalex.org/W2105636360","https://openalex.org/W2106053110","https://openalex.org/W2112530506","https://openalex.org/W2130556178","https://openalex.org/W2136261952","https://openalex.org/W2159583439","https://openalex.org/W2169495281","https://openalex.org/W6634840103","https://openalex.org/W6675751002","https://openalex.org/W6680332746","https://openalex.org/W6980340173"],"related_works":["https://openalex.org/W2795392346","https://openalex.org/W2969538544","https://openalex.org/W4246757943","https://openalex.org/W2085998272","https://openalex.org/W2351157934","https://openalex.org/W1595303882","https://openalex.org/W2182477562","https://openalex.org/W2571415506","https://openalex.org/W2526367648","https://openalex.org/W2108882154"],"abstract_inverted_index":{"The":[0],"performance":[1],"of":[2],"popular":[3],"and":[4],"classical":[5],"k-nearest":[6],"neighbor":[7,17],"classifier":[8,18],"depends":[9],"on":[10,39,55],"the":[11,49,56,71,76],"distance":[12],"metric.":[13],"Large":[14],"margin":[15],"nearest":[16],"using":[19],"gradient":[20,72],"optimization":[21],"method":[22,37,64,74],"is":[23],"prone":[24],"to":[25],"local":[26],"minima.":[27],"In":[28],"this":[29],"paper,":[30],"we":[31],"present":[32],"a":[33],"Mahalanobis":[34],"metric":[35],"learning":[36],"based":[38,73],"cutting":[40],"plane":[41],"algorithm":[42],"which":[43],"reduces":[44],"largely":[45],"constraints":[46],"for":[47],"solving":[48],"semidefinite":[50],"programming":[51],"problem.":[52],"Experimental":[53],"results":[54],"ITC":[57],"I":[58],"data":[59],"sets":[60],"show":[61],"that":[62],"our":[63],"can":[65],"achieve":[66],"promising":[67],"speedups":[68],"compared":[69],"with":[70],"under":[75],"similar":[77],"training,":[78],"test":[79],"error":[80],"rates.":[81]},"counts_by_year":[],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}