{"id":"https://openalex.org/W2623343763","doi":"https://doi.org/10.1109/mcse.2017.3151249","title":"Recursive Orthogonal Label Regression: A Framework for Semisupervised Dimension Reduction","display_name":"Recursive Orthogonal Label Regression: A Framework for Semisupervised Dimension Reduction","publication_year":2017,"publication_date":"2017-01-01","ids":{"openalex":"https://openalex.org/W2623343763","doi":"https://doi.org/10.1109/mcse.2017.3151249","mag":"2623343763"},"language":"en","primary_location":{"id":"doi:10.1109/mcse.2017.3151249","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mcse.2017.3151249","pdf_url":null,"source":{"id":"https://openalex.org/S107923245","display_name":"Computing in Science & Engineering","issn_l":"1521-9615","issn":["1521-9615","1558-366X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320061","host_organization_name":"AIP Publishing","host_organization_lineage":["https://openalex.org/P4310320061","https://openalex.org/P4310320257"],"host_organization_lineage_names":["AIP Publishing","American Institute of Physics"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computing in Science &amp; Engineering","raw_type":"journal-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/A5000959775","display_name":"Shangbing Gao","orcid":"https://orcid.org/0000-0002-3921-4511"},"institutions":[{"id":"https://openalex.org/I4210153869","display_name":"Huaiyin Institute of Technology","ror":"https://ror.org/0555ezg60","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210153869"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shangbing Gao","raw_affiliation_strings":["Southeast University and Huaiyin Institute of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Southeast University and Huaiyin Institute of Technology","institution_ids":["https://openalex.org/I4210153869"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039671101","display_name":"Qiaolin Ye","orcid":"https://orcid.org/0000-0002-8793-8610"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiaolin Ye","raw_affiliation_strings":["Key Laboratory of Image and Video Understanding for Social Safety (Nanjing University of Science and Technology)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Image and Video Understanding for Social Safety (Nanjing University of Science and Technology)","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036093909","display_name":"Limin Luo","orcid":"https://orcid.org/0000-0001-8954-1871"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Limin Luo","raw_affiliation_strings":["Southeast University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Southeast University","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044327434","display_name":"Zhigeng Pan","orcid":"https://orcid.org/0000-0003-0717-5850"},"institutions":[{"id":"https://openalex.org/I4210153869","display_name":"Huaiyin Institute of Technology","ror":"https://ror.org/0555ezg60","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210153869"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhigeng Pan","raw_affiliation_strings":["Huaiyin Institute of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huaiyin Institute of Technology","institution_ids":["https://openalex.org/I4210153869"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079583479","display_name":"Yunyang Yan","orcid":null},"institutions":[{"id":"https://openalex.org/I4210153869","display_name":"Huaiyin Institute of Technology","ror":"https://ror.org/0555ezg60","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210153869"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yunyang Yan","raw_affiliation_strings":["Huaiyin Institute of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huaiyin Institute of Technology","institution_ids":["https://openalex.org/I4210153869"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5085132445","display_name":"Hao Zheng","orcid":"https://orcid.org/0000-0003-0829-9660"},"institutions":[{"id":"https://openalex.org/I4210128418","display_name":"Nanjing Xiaozhuang University","ror":"https://ror.org/03fnv7n42","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210128418"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Zheng","raw_affiliation_strings":["Key Laboratory of Trusted Cloud Computing and Big Data Analysis, Nanjing Xiaozhuang University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Trusted Cloud Computing and Big Data Analysis, Nanjing Xiaozhuang University","institution_ids":["https://openalex.org/I4210128418"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.05909581,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"19","issue":"4","first_page":"30","last_page":"43"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9961000084877014,"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":0.9961000084877014,"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/T13114","display_name":"Image Processing Techniques and Applications","score":0.9918000102043152,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.9771999716758728,"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/regression","display_name":"Regression","score":0.7567803263664246},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.6297975182533264},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6060734391212463},{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.5752825736999512},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5698374509811401},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.5648320913314819},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.5307809114456177},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.509891152381897},{"id":"https://openalex.org/keywords/linear-discriminant-analysis","display_name":"Linear discriminant analysis","score":0.4773262143135071},{"id":"https://openalex.org/keywords/discriminant","display_name":"Discriminant","score":0.44770482182502747},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.44205355644226074},{"id":"https://openalex.org/keywords/polynomial-regression","display_name":"Polynomial regression","score":0.43790096044540405},{"id":"https://openalex.org/keywords/linear-regression","display_name":"Linear regression","score":0.4326504170894623},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.33343857526779175},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.3004249930381775}],"concepts":[{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.7567803263664246},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.6297975182533264},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6060734391212463},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.5752825736999512},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5698374509811401},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.5648320913314819},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.5307809114456177},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.509891152381897},{"id":"https://openalex.org/C69738355","wikidata":"https://www.wikidata.org/wiki/Q1228929","display_name":"Linear discriminant analysis","level":2,"score":0.4773262143135071},{"id":"https://openalex.org/C78397625","wikidata":"https://www.wikidata.org/wiki/Q192487","display_name":"Discriminant","level":2,"score":0.44770482182502747},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.44205355644226074},{"id":"https://openalex.org/C120068334","wikidata":"https://www.wikidata.org/wiki/Q45343","display_name":"Polynomial regression","level":3,"score":0.43790096044540405},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.4326504170894623},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.33343857526779175},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3004249930381775},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/mcse.2017.3151249","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mcse.2017.3151249","pdf_url":null,"source":{"id":"https://openalex.org/S107923245","display_name":"Computing in Science & Engineering","issn_l":"1521-9615","issn":["1521-9615","1558-366X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320061","host_organization_name":"AIP Publishing","host_organization_lineage":["https://openalex.org/P4310320061","https://openalex.org/P4310320257"],"host_organization_lineage_names":["AIP Publishing","American Institute of Physics"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computing in Science &amp; Engineering","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.7400000095367432,"display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1486189686","https://openalex.org/W1969204685","https://openalex.org/W2001141328","https://openalex.org/W2017368465","https://openalex.org/W2053186076","https://openalex.org/W2059998433","https://openalex.org/W2098048262","https://openalex.org/W2104290444","https://openalex.org/W2113590298","https://openalex.org/W2117553576","https://openalex.org/W2135496738","https://openalex.org/W2139823104","https://openalex.org/W2143103810","https://openalex.org/W2148603752","https://openalex.org/W2154455818","https://openalex.org/W2163584563","https://openalex.org/W2250542744","https://openalex.org/W3148981562","https://openalex.org/W6680434193","https://openalex.org/W6682494755","https://openalex.org/W6691622084"],"related_works":["https://openalex.org/W2350751952","https://openalex.org/W2362114017","https://openalex.org/W1999647744","https://openalex.org/W2794812819","https://openalex.org/W2114217318","https://openalex.org/W3147024994","https://openalex.org/W1978302214","https://openalex.org/W2587881214","https://openalex.org/W3104072235","https://openalex.org/W2374055396"],"abstract_inverted_index":{"Semisupervised":[0],"DR":[1],"techniques":[2],"using":[3,89],"virtual":[4],"label":[5,50,73,76,106],"regression":[6,51,65,77,91,107],"have":[7],"attracted":[8],"considerable":[9],"attention,":[10],"but":[11],"they":[12,83],"suffer":[13],"from":[14],"two":[15],"restrictions:":[16],"the":[17,26,56,85,112],"number":[18,27],"of":[19,28,67,87,105],"discriminant":[20],"directions":[21],"available":[22],"is":[23,43],"constrained":[24],"to":[25,45,98],"classes,":[29],"and":[30,75,100,115],"they're":[31],"nonorthogonal.":[32],"Traditional":[33],"methods":[34],"easily":[35],"address":[36,46],"these":[37,47],"problems.":[38],"However,":[39],"an":[40,95],"interesting":[41],"problem":[42],"how":[44],"restrictions":[48],"in":[49,78],"modelings.":[52],"To":[53],"do":[54],"this,":[55],"authors":[57],"developed":[58],"Recursive":[59],"Orthogonal":[60],"Label":[61],"Regression":[62],"(ROLR),":[63],"a":[64,79,102],"framework":[66],"semisupervised":[68,90],"dimension":[69],"reduction":[70],"that":[71],"uses":[72],"propagation":[74],"recursive":[80],"procedure.":[81],"Here,":[82],"illustrate":[84],"formulation":[86],"ROLR":[88,93],"encoding.":[92],"provides":[94],"unified":[96],"view":[97],"understand":[99],"explain":[101],"large":[103],"family":[104],"techniques.":[108],"Experimental":[109],"results":[110],"show":[111],"approach's":[113],"feasibility":[114],"effectiveness.":[116]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
