{"id":"https://openalex.org/W4285411253","doi":"https://doi.org/10.1109/tcyb.2022.3185588","title":"Learning Output Relevant Features by Joint Autoencoder","display_name":"Learning Output Relevant Features by Joint Autoencoder","publication_year":2022,"publication_date":"2022-07-14","ids":{"openalex":"https://openalex.org/W4285411253","doi":"https://doi.org/10.1109/tcyb.2022.3185588","pmid":"https://pubmed.ncbi.nlm.nih.gov/35834460"},"language":"en","primary_location":{"id":"doi:10.1109/tcyb.2022.3185588","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcyb.2022.3185588","pdf_url":null,"source":{"id":"https://openalex.org/S4210191041","display_name":"IEEE Transactions on Cybernetics","issn_l":"2168-2267","issn":["2168-2267","2168-2275"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Cybernetics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5062609303","display_name":"Shifu Yan","orcid":"https://orcid.org/0000-0002-3540-4756"},"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":true,"raw_author_name":"Shifu Yan","raw_affiliation_strings":["Key Laboratory of Smart Manufacturing in Energy Chemical Process, Ministry of Education, East China University of Science and Technology, Shanghai, China","Ministry of Education, Key Laboratory of Smart Manufacturing in Energy Chemical Process, East China University of Science and Technology, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Smart Manufacturing in Energy Chemical Process, Ministry of Education, East China University of Science and Technology, Shanghai, China","institution_ids":["https://openalex.org/I143593769"]},{"raw_affiliation_string":"Ministry of Education, Key Laboratory of Smart Manufacturing in Energy Chemical Process, East China University of Science and Technology, Shanghai, China","institution_ids":["https://openalex.org/I143593769"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5000809799","display_name":"Xuefeng Yan","orcid":"https://orcid.org/0000-0001-5622-8686"},"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":"Xuefeng Yan","raw_affiliation_strings":["Key Laboratory of Smart Manufacturing in Energy Chemical Process, Ministry of Education, East China University of Science and Technology, Shanghai, China","Ministry of Education, Key Laboratory of Smart Manufacturing in Energy Chemical Process, East China University of Science and Technology, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Smart Manufacturing in Energy Chemical Process, Ministry of Education, East China University of Science and Technology, Shanghai, China","institution_ids":["https://openalex.org/I143593769"]},{"raw_affiliation_string":"Ministry of Education, Key Laboratory of Smart Manufacturing in Energy Chemical Process, East China University of Science and Technology, Shanghai, China","institution_ids":["https://openalex.org/I143593769"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5062609303"],"corresponding_institution_ids":["https://openalex.org/I143593769"],"apc_list":null,"apc_paid":null,"fwci":0.1326,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.51603718,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"54","issue":"2","first_page":"1075","last_page":"1083"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9976999759674072,"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"}},"topics":[{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9976999759674072,"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/T10876","display_name":"Fault Detection and Control Systems","score":0.9973999857902527,"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"}},{"id":"https://openalex.org/T12676","display_name":"Machine Learning and ELM","score":0.9955000281333923,"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/autoencoder","display_name":"Autoencoder","score":0.8028086423873901},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7003148794174194},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6692726016044617},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6527698636054993},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6062459945678711},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.5891398191452026},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.5646553039550781},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.42392468452453613},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.40038251876831055},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.32033050060272217},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.2686254382133484},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16686344146728516},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.10474646091461182},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.0810961127281189}],"concepts":[{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.8028086423873901},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7003148794174194},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6692726016044617},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6527698636054993},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6062459945678711},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5891398191452026},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.5646553039550781},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.42392468452453613},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.40038251876831055},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.32033050060272217},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2686254382133484},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16686344146728516},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.10474646091461182},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0810961127281189},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tcyb.2022.3185588","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcyb.2022.3185588","pdf_url":null,"source":{"id":"https://openalex.org/S4210191041","display_name":"IEEE Transactions on Cybernetics","issn_l":"2168-2267","issn":["2168-2267","2168-2275"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Cybernetics","raw_type":"journal-article"},{"id":"pmid:35834460","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/35834460","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on cybernetics","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/1","score":0.6600000262260437,"display_name":"No poverty"}],"awards":[{"id":"https://openalex.org/G2354679411","display_name":null,"funder_award_id":"2020YFA0908303","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G6905653140","display_name":null,"funder_award_id":"21878081","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":48,"referenced_works":["https://openalex.org/W1562811233","https://openalex.org/W1565746575","https://openalex.org/W1571870753","https://openalex.org/W1981613567","https://openalex.org/W1989746184","https://openalex.org/W2005424446","https://openalex.org/W2008989859","https://openalex.org/W2009596443","https://openalex.org/W2015430519","https://openalex.org/W2030818161","https://openalex.org/W2040731319","https://openalex.org/W2042184006","https://openalex.org/W2043367171","https://openalex.org/W2044772846","https://openalex.org/W2071379517","https://openalex.org/W2081082425","https://openalex.org/W2088900896","https://openalex.org/W2101234009","https://openalex.org/W2110895726","https://openalex.org/W2128186735","https://openalex.org/W2139269942","https://openalex.org/W2153149612","https://openalex.org/W2158194116","https://openalex.org/W2344138609","https://openalex.org/W2581571072","https://openalex.org/W2585502432","https://openalex.org/W2735797020","https://openalex.org/W2754773664","https://openalex.org/W2809761809","https://openalex.org/W2885623963","https://openalex.org/W2907560147","https://openalex.org/W2944648179","https://openalex.org/W2952078227","https://openalex.org/W2952598456","https://openalex.org/W2963798770","https://openalex.org/W2964081830","https://openalex.org/W2990434508","https://openalex.org/W2994908203","https://openalex.org/W3011863222","https://openalex.org/W3018586685","https://openalex.org/W3039910281","https://openalex.org/W3160417254","https://openalex.org/W4205280876","https://openalex.org/W6631216910","https://openalex.org/W6675354045","https://openalex.org/W6682609908","https://openalex.org/W6683272254","https://openalex.org/W6754821620"],"related_works":["https://openalex.org/W3013693939","https://openalex.org/W2159052453","https://openalex.org/W2566616303","https://openalex.org/W3131327266","https://openalex.org/W4297051394","https://openalex.org/W2752972570","https://openalex.org/W2734887215","https://openalex.org/W2803255133","https://openalex.org/W2909431601","https://openalex.org/W3134175397"],"abstract_inverted_index":{"Classical":[0],"regression":[1,51],"is":[2,75,125],"a":[3,34,65,119],"supervised":[4,71],"task":[5],"that":[6],"uses":[7],"target":[8],"output":[9,20,59,79],"to":[10,33,44,77,96,127],"guide":[11],"the":[12,15,26,30,45,47,70,83,98,129,136,138,144],"modeling.":[13],"Generally,":[14],"original":[16,84],"input":[17],"contains":[18],"both":[19,89],"relevant":[21,60,80],"and":[22,72,91,101,141],"irrelevant":[23],"information,":[24],"whereas":[25],"latter":[27],"may":[28],"decrease":[29],"predictive":[31,48,90,130,139],"performance":[32,49,93,105,131,140],"certain":[35],"extent.":[36],"Without":[37],"prior":[38],"information":[39,42,61],"about":[40],"what":[41],"contributes":[43],"prediction,":[46],"of":[50,143],"models":[52],"can":[53,112],"be":[54,113],"improved":[55],"based":[56],"on":[57,106,148],"such":[58],"as":[62],"input.":[63,85],"Thus,":[64],"joint":[66],"autoencoder":[67],"(JAE)":[68],"combining":[69],"unsupervised":[73],"mechanisms":[74],"proposed":[76],"learn":[78,97],"features":[81],"from":[82],"In":[86,135],"this":[87,133],"way,":[88],"reconstructive":[92],"are":[94,146],"considered":[95],"essential":[99],"characteristics":[100],"avoid":[102],"poor":[103],"generalized":[104],"untrained":[107],"instances.":[108],"Meanwhile,":[109],"hierarchy":[110],"representations":[111],"learned":[114],"by":[115],"successive":[116],"JAEs":[117],"with":[118,151],"local":[120],"parameter":[121],"embedding":[122],"strategy,":[123],"which":[124],"presented":[126],"preserve":[128],"in":[132],"structure.":[134],"experiments,":[137],"robustness":[142],"proposal":[145],"verified":[147],"nine":[149],"datasets":[150],"different":[152],"sample":[153],"sizes.":[154]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}