{"id":"https://openalex.org/W2539576140","doi":"https://doi.org/10.1109/iske.2010.5680867","title":"Semi-supervised Transductive Discriminant Analysis","display_name":"Semi-supervised Transductive Discriminant Analysis","publication_year":2010,"publication_date":"2010-11-01","ids":{"openalex":"https://openalex.org/W2539576140","doi":"https://doi.org/10.1109/iske.2010.5680867","mag":"2539576140"},"language":"en","primary_location":{"id":"doi:10.1109/iske.2010.5680867","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iske.2010.5680867","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 IEEE International Conference on Intelligent Systems and Knowledge Engineering","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/A5100358257","display_name":"Yi Li","orcid":"https://orcid.org/0000-0001-9865-5141"},"institutions":[{"id":"https://openalex.org/I4210132223","display_name":"Zhejiang Radio and Television University","ror":"https://ror.org/02kpaqs60","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210132223"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yi Li","raw_affiliation_strings":["School of Information and Engineering, Zhejiang Radio and TV University, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Information and Engineering, Zhejiang Radio and TV University, Hangzhou, China","institution_ids":["https://openalex.org/I4210132223"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5084922351","display_name":"Xuesong Yin","orcid":null},"institutions":[{"id":"https://openalex.org/I4210132223","display_name":"Zhejiang Radio and Television University","ror":"https://ror.org/02kpaqs60","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210132223"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuesong Yin","raw_affiliation_strings":["School of Information and Engineering, Zhejiang Radio and TV University, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Information and Engineering, Zhejiang Radio and TV University, Hangzhou, China","institution_ids":["https://openalex.org/I4210132223"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5100358257"],"corresponding_institution_ids":["https://openalex.org/I4210132223"],"apc_list":null,"apc_paid":null,"fwci":0.6374,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.74145517,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"27","issue":null,"first_page":"291","last_page":"295"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9972000122070312,"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":0.9972000122070312,"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/T10320","display_name":"Neural Networks and Applications","score":0.9605000019073486,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9404000043869019,"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/overfitting","display_name":"Overfitting","score":0.8368908762931824},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.8007034063339233},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7102934122085571},{"id":"https://openalex.org/keywords/linear-discriminant-analysis","display_name":"Linear discriminant analysis","score":0.6536163091659546},{"id":"https://openalex.org/keywords/discriminant","display_name":"Discriminant","score":0.6338012218475342},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6115120053291321},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6075915098190308},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.575127124786377},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.5020570755004883},{"id":"https://openalex.org/keywords/semi-supervised-learning","display_name":"Semi-supervised learning","score":0.4591298997402191},{"id":"https://openalex.org/keywords/multiple-discriminant-analysis","display_name":"Multiple discriminant analysis","score":0.43608608841896057},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.43293625116348267},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4169577658176422},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3410700857639313},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.07173514366149902}],"concepts":[{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.8368908762931824},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.8007034063339233},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7102934122085571},{"id":"https://openalex.org/C69738355","wikidata":"https://www.wikidata.org/wiki/Q1228929","display_name":"Linear discriminant analysis","level":2,"score":0.6536163091659546},{"id":"https://openalex.org/C78397625","wikidata":"https://www.wikidata.org/wiki/Q192487","display_name":"Discriminant","level":2,"score":0.6338012218475342},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6115120053291321},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6075915098190308},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.575127124786377},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.5020570755004883},{"id":"https://openalex.org/C58973888","wikidata":"https://www.wikidata.org/wiki/Q1041418","display_name":"Semi-supervised learning","level":2,"score":0.4591298997402191},{"id":"https://openalex.org/C58596280","wikidata":"https://www.wikidata.org/wiki/Q28324849","display_name":"Multiple discriminant analysis","level":3,"score":0.43608608841896057},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.43293625116348267},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4169577658176422},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3410700857639313},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.07173514366149902},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iske.2010.5680867","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iske.2010.5680867","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 IEEE International Conference on Intelligent Systems and Knowledge Engineering","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.7400000095367432}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W333587792","https://openalex.org/W1490760466","https://openalex.org/W1510147702","https://openalex.org/W1564277727","https://openalex.org/W1592096085","https://openalex.org/W1969204685","https://openalex.org/W1981791883","https://openalex.org/W2062112832","https://openalex.org/W2105055468","https://openalex.org/W2108263194","https://openalex.org/W2117553576","https://openalex.org/W2121647436","https://openalex.org/W2139224176","https://openalex.org/W2145357920","https://openalex.org/W2148694408","https://openalex.org/W2163584563","https://openalex.org/W2799061466","https://openalex.org/W4230946174","https://openalex.org/W4285719527","https://openalex.org/W4292933682","https://openalex.org/W7034449035"],"related_works":["https://openalex.org/W3211783303","https://openalex.org/W2063246903","https://openalex.org/W2141981133","https://openalex.org/W1978302214","https://openalex.org/W2350751952","https://openalex.org/W1984472287","https://openalex.org/W2124643900","https://openalex.org/W2375208160","https://openalex.org/W2368666353","https://openalex.org/W2900942978"],"abstract_inverted_index":{"When":[0],"there":[1],"is":[2,70,89],"no":[3],"sufficient":[4],"labeled":[5,59],"instances,":[6],"supervised":[7],"dimensionality":[8,35,94],"reduction":[9,36,95],"methods":[10],"tend":[11],"to":[12,16,25,57,91],"perform":[13],"poorly":[14],"due":[15],"overfitting.":[17],"In":[18,29],"such":[19],"cases,":[20],"unlabeled":[21,53],"instances":[22,54,60],"are":[23],"used":[24],"improve":[26],"the":[27,46,52],"performance.":[28],"this":[30],"paper,":[31],"we":[32],"propose":[33],"a":[34,74,80],"method":[37],"called":[38],"semi-supervised":[39],"TransductIve":[40],"Discriminant":[41],"Analysis":[42],"(TIDA)":[43],"which":[44],"preserves":[45],"global":[47],"and":[48,72],"geometrical":[49],"structure":[50],"of":[51,83],"in":[55,61],"addition":[56],"separating":[58],"different":[62],"classes":[63],"from":[64],"each":[65],"other.":[66],"The":[67],"proposed":[68],"algorithm":[69],"efficient":[71],"has":[73],"closed":[75],"form":[76],"solution.":[77],"Experiments":[78],"on":[79],"broad":[81],"range":[82],"data":[84],"sets":[85],"show":[86],"that":[87],"TIDA":[88],"superior":[90],"many":[92],"relevant":[93],"methods.":[96]},"counts_by_year":[{"year":2015,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}