{"id":"https://openalex.org/W2978979171","doi":"https://doi.org/10.1109/ijcnn.2019.8851712","title":"Discriminative Regularization with Conditional Generative Adversarial Nets for Semi-Supervised Learning","display_name":"Discriminative Regularization with Conditional Generative Adversarial Nets for Semi-Supervised Learning","publication_year":2019,"publication_date":"2019-07-01","ids":{"openalex":"https://openalex.org/W2978979171","doi":"https://doi.org/10.1109/ijcnn.2019.8851712","mag":"2978979171"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2019.8851712","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2019.8851712","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 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/A5101868563","display_name":"Qianqian Xie","orcid":"https://orcid.org/0000-0002-9588-7454"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Qianqian Xie","raw_affiliation_strings":["School of Computer Science, Wuhan University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102012008","display_name":"Min Peng","orcid":"https://orcid.org/0000-0001-7445-5567"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Min Peng","raw_affiliation_strings":["School of Computer Science, Wuhan University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018254776","display_name":"Jimin Huang","orcid":"https://orcid.org/0000-0002-3501-3907"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jimin Huang","raw_affiliation_strings":["School of Computer Science, Wuhan University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015829772","display_name":"Bin Wang","orcid":"https://orcid.org/0000-0001-9760-8343"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bin Wang","raw_affiliation_strings":["Xiaomi Inc., Beijing, China"],"affiliations":[{"raw_affiliation_string":"Xiaomi Inc., Beijing, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100403969","display_name":"Hua Wang","orcid":"https://orcid.org/0000-0002-8465-0996"},"institutions":[{"id":"https://openalex.org/I71270174","display_name":"Victoria University","ror":"https://ror.org/04j757h98","country_code":"AU","type":"education","lineage":["https://openalex.org/I71270174"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Hua Wang","raw_affiliation_strings":["Centre for Applied Informatics, Victoria University, Melbourne, Australia"],"affiliations":[{"raw_affiliation_string":"Centre for Applied Informatics, Victoria University, Melbourne, Australia","institution_ids":["https://openalex.org/I71270174"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5101868563"],"corresponding_institution_ids":["https://openalex.org/I37461747"],"apc_list":null,"apc_paid":null,"fwci":0.1022,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.45016204,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"2011","issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9997000098228455,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9997000098228455,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.9959999918937683,"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":0.9944999814033508,"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/discriminative-model","display_name":"Discriminative model","score":0.8163151741027832},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6553891897201538},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.650987446308136},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5777319669723511},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5636805295944214},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.5290162563323975},{"id":"https://openalex.org/keywords/semi-supervised-learning","display_name":"Semi-supervised learning","score":0.5122568011283875},{"id":"https://openalex.org/keywords/data-point","display_name":"Data point","score":0.47790560126304626},{"id":"https://openalex.org/keywords/laplacian-matrix","display_name":"Laplacian matrix","score":0.4624076187610626},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.46078407764434814},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4059256315231323},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3816126585006714},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.3084172010421753},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.16247200965881348}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.8163151741027832},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6553891897201538},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.650987446308136},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5777319669723511},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5636805295944214},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.5290162563323975},{"id":"https://openalex.org/C58973888","wikidata":"https://www.wikidata.org/wiki/Q1041418","display_name":"Semi-supervised learning","level":2,"score":0.5122568011283875},{"id":"https://openalex.org/C21080849","wikidata":"https://www.wikidata.org/wiki/Q13611879","display_name":"Data point","level":2,"score":0.47790560126304626},{"id":"https://openalex.org/C115178988","wikidata":"https://www.wikidata.org/wiki/Q772067","display_name":"Laplacian matrix","level":3,"score":0.4624076187610626},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.46078407764434814},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4059256315231323},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3816126585006714},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.3084172010421753},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.16247200965881348}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/ijcnn.2019.8851712","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2019.8851712","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},{"id":"pmh:oai:eprints.vu.edu.au:42671","is_oa":false,"landing_page_url":"https://vuir.vu.edu.au/42671/","pdf_url":null,"source":{"id":"https://openalex.org/S4306400215","display_name":"Victoria University Research Repository (Victoria University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I41156924","host_organization_name":"Victoria University of Wellington","host_organization_lineage":["https://openalex.org/I41156924"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"PeerReviewed"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.7099999785423279}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":77,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W769612788","https://openalex.org/W830076066","https://openalex.org/W1536452289","https://openalex.org/W1564492259","https://openalex.org/W1966949944","https://openalex.org/W1983320747","https://openalex.org/W2022508996","https://openalex.org/W2030728354","https://openalex.org/W2099471712","https://openalex.org/W2104290444","https://openalex.org/W2108501770","https://openalex.org/W2112796928","https://openalex.org/W2125389028","https://openalex.org/W2145094598","https://openalex.org/W2163605009","https://openalex.org/W2166093887","https://openalex.org/W2173520492","https://openalex.org/W2178768799","https://openalex.org/W2280377497","https://openalex.org/W2335728318","https://openalex.org/W2340339255","https://openalex.org/W2411541852","https://openalex.org/W2519536754","https://openalex.org/W2551446786","https://openalex.org/W2556707115","https://openalex.org/W2596763562","https://openalex.org/W2607239473","https://openalex.org/W2613718673","https://openalex.org/W2619371851","https://openalex.org/W2768252793","https://openalex.org/W2798001063","https://openalex.org/W2798523175","https://openalex.org/W2809551588","https://openalex.org/W2949416428","https://openalex.org/W2952229419","https://openalex.org/W2962808998","https://openalex.org/W2963043971","https://openalex.org/W2963170156","https://openalex.org/W2963250052","https://openalex.org/W2963373786","https://openalex.org/W2963425170","https://openalex.org/W2963684088","https://openalex.org/W2964040467","https://openalex.org/W2964218010","https://openalex.org/W2964231450","https://openalex.org/W2997574889","https://openalex.org/W2997701990","https://openalex.org/W3001208697","https://openalex.org/W3118608800","https://openalex.org/W4293577678","https://openalex.org/W4294541410","https://openalex.org/W4320013936","https://openalex.org/W6620707391","https://openalex.org/W6622262455","https://openalex.org/W6623329352","https://openalex.org/W6632121129","https://openalex.org/W6675747103","https://openalex.org/W6675944832","https://openalex.org/W6678815747","https://openalex.org/W6681096077","https://openalex.org/W6684191040","https://openalex.org/W6684805783","https://openalex.org/W6685352114","https://openalex.org/W6685777725","https://openalex.org/W6703116779","https://openalex.org/W6714590955","https://openalex.org/W6718379498","https://openalex.org/W6726794401","https://openalex.org/W6729308238","https://openalex.org/W6730200498","https://openalex.org/W6738597727","https://openalex.org/W6745694482","https://openalex.org/W6745891138","https://openalex.org/W6751136067","https://openalex.org/W6752527525","https://openalex.org/W6787972765"],"related_works":["https://openalex.org/W4396941953","https://openalex.org/W2987280934","https://openalex.org/W4241564561","https://openalex.org/W2894889024","https://openalex.org/W2017735937","https://openalex.org/W2186210338","https://openalex.org/W4289419876","https://openalex.org/W2146245123","https://openalex.org/W2896696294","https://openalex.org/W1529879082"],"abstract_inverted_index":{"Existing":[0],"generative":[1,86],"adversarial":[2,87],"networks":[3],"(GANs)":[4],"with":[5,84],"manifold":[6,31,115],"regularization":[7,79,119],"for":[8,43,53,81,137],"semi-supervised":[9,20,82],"learning":[10,21,83],"(SSL)":[11],"have":[12],"shown":[13],"promising":[14],"performance":[15,178],"in":[16,46,56,67,140],"image":[17],"generation":[18],"and":[19,133],"(SSL),":[22],"which":[23],"penalize":[24],"the":[25,34,38,93,108,117,121,128,151,156,161],"smoothness":[26,35,39],"of":[27,110,130,163],"classifier":[28,122,164],"over":[29],"data":[30,44,54,99,138],"based":[32],"on":[33,127,168],"assumption.":[36],"However,":[37],"assumption":[40],"is":[41,104],"valid":[42],"points":[45,55,139],"high":[47],"density":[48,58,69],"region":[49],"while":[50],"not":[51],"hold":[52],"low":[57,68],"region,":[59],"thus":[60],"they":[61],"tend":[62],"to":[63,106,124],"misclassify":[64],"boundary":[65],"instances":[66],"region.":[70],"In":[71,90],"this":[72],"paper,":[73],"we":[74],"propose":[75],"a":[76],"novel":[77],"discriminative":[78,94,118],"method":[80,145,174],"conditional":[85,98],"nets":[88],"(CGANs).":[89],"our":[91,144,173],"method,":[92],"information":[95],"from":[96,113],"class":[97],"distribution":[100],"captured":[101],"by":[102],"CGANs":[103],"utilized":[105],"improve":[107],"discrimination":[109],"classifier.":[111],"Different":[112],"regular":[114],"regularization,":[116],"encourages":[120],"invariance":[123],"local":[125],"perturbations":[126],"sub-manifold":[129],"each":[131],"cluster,":[132],"distinct":[134],"classification":[135],"outputs":[136],"different":[141],"clusters.":[142],"Moreover,":[143],"can":[146,175],"be":[147],"easily":[148],"implemented":[149],"via":[150],"stochastic":[152],"approximation":[153],"without":[154],"constructing":[155],"Laplacian":[157],"graph":[158],"or":[159],"computing":[160],"Jacobian":[162],"explicitly.":[165],"Experimental":[166],"results":[167],"benchmark":[169],"datasets":[170],"show":[171],"that":[172],"achieve":[176],"competitive":[177],"against":[179],"previous":[180],"advanced":[181],"methods.":[182]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}
