{"id":"https://openalex.org/W2004104413","doi":"https://doi.org/10.1109/cecnet.2013.6703276","title":"An algorithm research of supervised LLE based on mahalanobis distance and extreme learning machine","display_name":"An algorithm research of supervised LLE based on mahalanobis distance and extreme learning machine","publication_year":2013,"publication_date":"2013-11-01","ids":{"openalex":"https://openalex.org/W2004104413","doi":"https://doi.org/10.1109/cecnet.2013.6703276","mag":"2004104413"},"language":"en","primary_location":{"id":"doi:10.1109/cecnet.2013.6703276","doi":"https://doi.org/10.1109/cecnet.2013.6703276","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cecnet.2013.6703276","pdf_url":null,"source":{"id":"https://openalex.org/S7407087280","display_name":"International Conference on Consumer Electronics, Communications and Networks (CECNet)","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":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 3rd International Conference on Consumer Electronics, Communications and Networks","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"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/A5112122255","display_name":"Lingmin He","orcid":"https://orcid.org/0009-0002-6222-0765","observed_orcids":["https://orcid.org/0009-0002-6222-0765"]},"institutions":[{"id":"https://openalex.org/I55538621","display_name":"China Jiliang University","ror":"https://ror.org/05v1y0t93","country_code":"CN","type":"education","lineage":["https://openalex.org/I55538621"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ling-Min He","raw_affiliation_strings":["College of information engineering, China Jiliang University, Hangzhou, China","Coll. of Inf. Eng., China JiLiang Univ., Hangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of information engineering, China Jiliang University, Hangzhou, China","institution_ids":["https://openalex.org/I55538621"]},{"raw_affiliation_string":"Coll. of Inf. Eng., China JiLiang Univ., Hangzhou, China","institution_ids":["https://openalex.org/I55538621"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Wei Jin","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I55538621","display_name":"China Jiliang University","ror":"https://ror.org/05v1y0t93","country_code":"CN","type":"education","lineage":["https://openalex.org/I55538621"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Jin","raw_affiliation_strings":["College of information engineering, China Jiliang University, Hangzhou, China","Coll. of Inf. Eng., China JiLiang Univ., Hangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of information engineering, China Jiliang University, Hangzhou, China","institution_ids":["https://openalex.org/I55538621"]},{"raw_affiliation_string":"Coll. of Inf. Eng., China JiLiang Univ., Hangzhou, China","institution_ids":["https://openalex.org/I55538621"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102221291","display_name":"Yang Xiao-bin","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I55538621","display_name":"China Jiliang University","ror":"https://ror.org/05v1y0t93","country_code":"CN","type":"education","lineage":["https://openalex.org/I55538621"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiao-Bin Yang","raw_affiliation_strings":["College of information engineering, China Jiliang University, Hangzhou, China","Coll. of Inf. Eng., China JiLiang Univ., Hangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of information engineering, China Jiliang University, Hangzhou, China","institution_ids":["https://openalex.org/I55538621"]},{"raw_affiliation_string":"Coll. of Inf. Eng., China JiLiang Univ., Hangzhou, China","institution_ids":["https://openalex.org/I55538621"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5046234442","display_name":"Kangjian Wang","orcid":"https://orcid.org/0000-0002-5549-4293","observed_orcids":["https://orcid.org/0000-0002-5549-4293"]},"institutions":[{"id":"https://openalex.org/I55538621","display_name":"China Jiliang University","ror":"https://ror.org/05v1y0t93","country_code":"CN","type":"education","lineage":["https://openalex.org/I55538621"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kang-Jian Wang","raw_affiliation_strings":["College of information engineering, China Jiliang University, Hangzhou, China","Coll. of Inf. Eng., China JiLiang Univ., Hangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of information engineering, China Jiliang University, Hangzhou, China","institution_ids":["https://openalex.org/I55538621"]},{"raw_affiliation_string":"Coll. of Inf. Eng., China JiLiang Univ., Hangzhou, China","institution_ids":["https://openalex.org/I55538621"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I55538621"],"apc_list":null,"apc_paid":null,"fwci":0.2109,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.35576114,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":88,"max":93},"biblio":{"volume":"25","issue":null,"first_page":"76","last_page":"79"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.8335000276565552,"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":0.8335000276565552,"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/T12676","display_name":"Machine Learning and ELM","score":0.15649999678134918,"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/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.002899999963119626,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/mahalanobis-distance","display_name":"Mahalanobis distance","score":0.9739999771118164},{"id":"https://openalex.org/keywords/extreme-learning-machine","display_name":"extreme learning machine","score":0.9829999804496765},{"id":"https://openalex.org/keywords/nonlinear-dimensionality-reduction","display_name":"nonlinear dimensionality reduction","score":0.968999981880188},{"id":"https://openalex.org/keywords/neighborhood-choice","display_name":"neighborhood selection","score":0.6610000133514404},{"id":"https://openalex.org/keywords/fault-pattern-recognition","display_name":"fault pattern recognition","score":0.7300000190734863},{"id":"https://openalex.org/keywords/high-dimensional-data","display_name":"high-dimensional data","score":0.9300000071525574},{"id":"https://openalex.org/keywords/class-information","display_name":"class information","score":0.33000001311302185}],"concepts":[{"id":"https://openalex.org/C1921717","wikidata":"https://www.wikidata.org/wiki/Q1334846","display_name":"Mahalanobis distance","level":2,"score":0.887293815612793},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6912871599197388},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5879805088043213},{"id":"https://openalex.org/C2780150128","wikidata":"https://www.wikidata.org/wiki/Q21948731","display_name":"Extreme learning machine","level":3,"score":0.4889327585697174},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.44938910007476807},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4126889407634735},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3411093056201935},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.10693567991256714}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cecnet.2013.6703276","doi":"https://doi.org/10.1109/cecnet.2013.6703276","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cecnet.2013.6703276","pdf_url":null,"source":{"id":"https://openalex.org/S7407087280","display_name":"International Conference on Consumer Electronics, Communications and Networks (CECNet)","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":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 3rd International Conference on Consumer Electronics, Communications and Networks","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W1978959572","https://openalex.org/W1979182421","https://openalex.org/W1990938413","https://openalex.org/W1996633793","https://openalex.org/W1997575533","https://openalex.org/W2004786826","https://openalex.org/W2018841310","https://openalex.org/W2024464446","https://openalex.org/W2048452128","https://openalex.org/W2062112832","https://openalex.org/W2065411115","https://openalex.org/W2072026719","https://openalex.org/W2111072639","https://openalex.org/W2140492997","https://openalex.org/W2386156469","https://openalex.org/W6983238977"],"related_works":["https://openalex.org/W1755467358","https://openalex.org/W7096826525","https://openalex.org/W7095956652","https://openalex.org/W2064956994","https://openalex.org/W2118706687","https://openalex.org/W93853188","https://openalex.org/W7097443628","https://openalex.org/W2545189195","https://openalex.org/W2024464446","https://openalex.org/W2079562675"],"abstract_inverted_index":{"The":[0,43,101],"Locally":[1],"Linear":[2],"Embedding":[3],"(LLE)":[4],"is":[5,21,84],"one":[6],"of":[7,27],"the":[8,24,28,39,60,67,71,88,92],"efficient":[9],"nonlinear":[10],"dimensionality":[11],"reduction":[12,109],"techniques.":[13],"But":[14],"for":[15,112],"some":[16],"high":[17],"dimensional":[18],"data,":[19],"it":[20],"not":[22,36],"taking":[23],"class":[25,52],"information":[26,76],"data":[29,54,90],"into":[30],"account":[31],"and":[32,55,74,110,114],"Euclidean":[33],"distance":[34],"can":[35],"accurately":[37],"reflect":[38],"similarity":[40],"among":[41],"samples.":[42],"paper":[44],"proposes":[45],"an":[46],"improved":[47],"Supervised":[48],"LLE":[49],"which":[50,95],"combines":[51],"labeled":[53],"Mahalanobis":[56,64,72],"Distance":[57,65,73],"(MSP-LLE).":[58],"First,":[59],"approach":[61],"learns":[62],"a":[63],"from":[66],"existing":[68],"data.":[69,116],"Then":[70],"label":[75],"are":[77],"combined":[78],"to":[79,86,91],"choose":[80],"neighborhoods.":[81],"Finally,":[82],"ELM":[83],"using":[85],"map":[87],"unlabeled":[89],"feature":[93],"space,":[94],"easily":[96],"implement":[97],"fault":[98],"pattern":[99],"recognition.":[100],"experiment":[102],"result":[103],"shows":[104],"its":[105],"good":[106],"performance":[107],"on":[108],"recognition":[111],"high-dimensional":[113],"similar":[115]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2016,"cited_by_count":1}],"updated_date":"2026-10-16T09:59:22.235173","created_date":"2016-06-24T00:00:00"}
