{"id":"https://openalex.org/W2550156111","doi":"https://doi.org/10.1109/ijcnn.2016.7727218","title":"Co-regularized least square regression for multi-view multi-class classification","display_name":"Co-regularized least square regression for multi-view multi-class classification","publication_year":2016,"publication_date":"2016-07-01","ids":{"openalex":"https://openalex.org/W2550156111","doi":"https://doi.org/10.1109/ijcnn.2016.7727218","mag":"2550156111"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2016.7727218","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2016.7727218","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 International Joint Conference on Neural Networks (IJCNN)","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/A5023655697","display_name":"Chao Lan","orcid":"https://orcid.org/0000-0003-2526-7206"},"institutions":[{"id":"https://openalex.org/I146416000","display_name":"University of Kansas","ror":"https://ror.org/001tmjg57","country_code":"US","type":"education","lineage":["https://openalex.org/I146416000"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Chao Lan","raw_affiliation_strings":["EECS Department, University of Kansas, Lawrence, Kansas"],"affiliations":[{"raw_affiliation_string":"EECS Department, University of Kansas, Lawrence, Kansas","institution_ids":["https://openalex.org/I146416000"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002647742","display_name":"Yujie Deng","orcid":"https://orcid.org/0000-0003-3609-4494"},"institutions":[{"id":"https://openalex.org/I146416000","display_name":"University of Kansas","ror":"https://ror.org/001tmjg57","country_code":"US","type":"education","lineage":["https://openalex.org/I146416000"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yujie Deng","raw_affiliation_strings":["EECS Department and Department of Mathematics, University of Kansas, Lawrence, Kansas"],"affiliations":[{"raw_affiliation_string":"EECS Department and Department of Mathematics, University of Kansas, Lawrence, Kansas","institution_ids":["https://openalex.org/I146416000"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100418684","display_name":"Xiaoli Li","orcid":"https://orcid.org/0000-0002-0762-6562"},"institutions":[{"id":"https://openalex.org/I146416000","display_name":"University of Kansas","ror":"https://ror.org/001tmjg57","country_code":"US","type":"education","lineage":["https://openalex.org/I146416000"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiaoli Li","raw_affiliation_strings":["EECS Department, University of Kansas, Lawrence, Kansas"],"affiliations":[{"raw_affiliation_string":"EECS Department, University of Kansas, Lawrence, Kansas","institution_ids":["https://openalex.org/I146416000"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5105352906","display_name":"Jun Huan","orcid":"https://orcid.org/0000-0003-4929-2617"},"institutions":[{"id":"https://openalex.org/I146416000","display_name":"University of Kansas","ror":"https://ror.org/001tmjg57","country_code":"US","type":"education","lineage":["https://openalex.org/I146416000"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jun Huan","raw_affiliation_strings":["EECS Department, University of Kansas, Lawrence, Kansas"],"affiliations":[{"raw_affiliation_string":"EECS Department, University of Kansas, Lawrence, Kansas","institution_ids":["https://openalex.org/I146416000"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5023655697"],"corresponding_institution_ids":["https://openalex.org/I146416000"],"apc_list":null,"apc_paid":null,"fwci":0.334,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.67323409,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":"1","issue":null,"first_page":"342","last_page":"347"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9991999864578247,"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":0.9991999864578247,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9947999715805054,"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/T12676","display_name":"Machine Learning and ELM","score":0.9936000108718872,"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/coding","display_name":"Coding (social sciences)","score":0.6221329569816589},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6023960113525391},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.5486012101173401},{"id":"https://openalex.org/keywords/naive-bayes-classifier","display_name":"Naive Bayes classifier","score":0.5231643915176392},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5192087292671204},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5136048793792725},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.4646925628185272},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.45210593938827515},{"id":"https://openalex.org/keywords/bch-code","display_name":"BCH code","score":0.4453003406524658},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.42290470004081726},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.41792765259742737},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.39328399300575256},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3832140862941742},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.35700953006744385},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.32539618015289307},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.27983909845352173},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.23490867018699646},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.17632892727851868}],"concepts":[{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.6221329569816589},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6023960113525391},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.5486012101173401},{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.5231643915176392},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5192087292671204},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5136048793792725},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.4646925628185272},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.45210593938827515},{"id":"https://openalex.org/C42276685","wikidata":"https://www.wikidata.org/wiki/Q795705","display_name":"BCH code","level":3,"score":0.4453003406524658},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.42290470004081726},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.41792765259742737},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.39328399300575256},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3832140862941742},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.35700953006744385},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.32539618015289307},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.27983909845352173},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.23490867018699646},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.17632892727851868},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn.2016.7727218","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2016.7727218","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 International Joint Conference on Neural Networks (IJCNN)","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":63,"referenced_works":["https://openalex.org/W71672857","https://openalex.org/W158976495","https://openalex.org/W384942176","https://openalex.org/W1120607479","https://openalex.org/W1483660231","https://openalex.org/W1504554469","https://openalex.org/W1580142630","https://openalex.org/W1588401315","https://openalex.org/W1595222087","https://openalex.org/W1596717185","https://openalex.org/W1670132599","https://openalex.org/W1670608554","https://openalex.org/W1676820704","https://openalex.org/W1974455604","https://openalex.org/W1989027995","https://openalex.org/W2006151125","https://openalex.org/W2019575783","https://openalex.org/W2037495825","https://openalex.org/W2048679005","https://openalex.org/W2049292654","https://openalex.org/W2072942628","https://openalex.org/W2080772494","https://openalex.org/W2085789144","https://openalex.org/W2100942256","https://openalex.org/W2105102731","https://openalex.org/W2107021927","https://openalex.org/W2126116132","https://openalex.org/W2128028519","https://openalex.org/W2128333053","https://openalex.org/W2133232758","https://openalex.org/W2133348086","https://openalex.org/W2146407312","https://openalex.org/W2154415691","https://openalex.org/W2155342973","https://openalex.org/W2158703881","https://openalex.org/W2161329297","https://openalex.org/W2166338096","https://openalex.org/W2167665791","https://openalex.org/W2170308301","https://openalex.org/W2170615026","https://openalex.org/W2201792562","https://openalex.org/W2207631730","https://openalex.org/W2246933272","https://openalex.org/W2787592560","https://openalex.org/W4230590910","https://openalex.org/W4233372644","https://openalex.org/W4285719527","https://openalex.org/W4300632884","https://openalex.org/W6602930527","https://openalex.org/W6606470850","https://openalex.org/W6627083702","https://openalex.org/W6635058605","https://openalex.org/W6635498880","https://openalex.org/W6636883489","https://openalex.org/W6637189863","https://openalex.org/W6678739253","https://openalex.org/W6679327959","https://openalex.org/W6679629151","https://openalex.org/W6682991666","https://openalex.org/W6683255826","https://openalex.org/W6683355845","https://openalex.org/W6747995932","https://openalex.org/W6982939652"],"related_works":["https://openalex.org/W2912502034","https://openalex.org/W2319574489","https://openalex.org/W2035908476","https://openalex.org/W2506979107","https://openalex.org/W4239727543","https://openalex.org/W2612882049","https://openalex.org/W2284101512","https://openalex.org/W1604083761","https://openalex.org/W2262711716","https://openalex.org/W1577730984"],"abstract_inverted_index":{"Many":[0],"classification":[1],"problems":[2],"involve":[3],"instances":[4],"that":[5,25],"are":[6],"unlabeled,":[7],"multi-view":[8,49],"and":[9,57,82],"multi-class.":[10],"However,":[11],"few":[12],"technique":[13],"has":[14],"been":[15],"benchmarked":[16],"for":[17,47,72],"this":[18,35],"complex":[19],"scenario,":[20],"with":[21,31],"a":[22,93],"notable":[23],"exception":[24],"combines":[26],"co-trained":[27],"naive":[28],"bayes":[29],"(CoT-NB)":[30],"BCH":[32,83],"coding.":[33],"In":[34],"paper,":[36],"we":[37],"benchmark":[38],"the":[39],"performance":[40],"of":[41],"co-regularized":[42],"least":[43],"square":[44],"regression":[45],"(CoR-LS)":[46],"semi-supervised":[48],"multi-class":[50],"classification.":[51],"We":[52,69],"find":[53,71],"it":[54],"performed":[55],"consistently":[56],"significantly":[58],"better":[59],"than":[60],"CoT-NB":[61],"over":[62],"eight":[63],"data":[64,80,89],"sets":[65,81],"at":[66],"different":[67],"scales.":[68],"also":[70],"CoR-LS":[73],"identity":[74],"coding":[75,84,95],"is":[76,85],"optimal":[77,86],"on":[78,87],"large":[79],"small":[88],"sets.":[90],"Optimal":[91],"scoring,":[92],"data-dependent":[94],"scheme,":[96],"often":[97],"provides":[98],"near-optimal":[99],"performance.":[100]},"counts_by_year":[{"year":2019,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
