{"id":"https://openalex.org/W2965052260","doi":"https://doi.org/10.24963/ijcai.2019/453","title":"Improving representation learning in autoencoders via multidimensional interpolation and dual regularizations","display_name":"Improving representation learning in autoencoders via multidimensional interpolation and dual regularizations","publication_year":2019,"publication_date":"2019-07-28","ids":{"openalex":"https://openalex.org/W2965052260","doi":"https://doi.org/10.24963/ijcai.2019/453","mag":"2965052260"},"language":"en","primary_location":{"id":"doi:10.24963/ijcai.2019/453","doi":"https://doi.org/10.24963/ijcai.2019/453","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2019/453","pdf_url":"https://www.ijcai.org/proceedings/2019/0453.pdf","source":{"id":"https://openalex.org/S4306419999","display_name":"International Joint Conference on Artificial Intelligence","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://www.ijcai.org/proceedings/2019/0453.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5088726237","display_name":"Sheng Qian","orcid":"https://orcid.org/0000-0003-4337-8532","observed_orcids":["https://orcid.org/0000-0003-4337-8532"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sheng Qian","raw_affiliation_strings":["Huawei Device Company Limited"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huawei Device Company Limited","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006031277","display_name":"Guanyue Li","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guanyue Li","raw_affiliation_strings":["School of Computer Science and Engineering, South China University of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, South China University of Technology","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100625023","display_name":"Wenming Cao","orcid":"https://orcid.org/0000-0002-6908-8018","observed_orcids":["https://orcid.org/0000-0002-6908-8018"]},"institutions":[{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"education","lineage":["https://openalex.org/I168719708"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Wen-Ming Cao","raw_affiliation_strings":["Department of Computer Science, City University of Hong Kong"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, City University of Hong Kong","institution_ids":["https://openalex.org/I168719708"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101660672","display_name":"Cheng Liu","orcid":"https://orcid.org/0000-0002-7204-7030","observed_orcids":["https://orcid.org/0000-0002-7204-7030"]},"institutions":[{"id":"https://openalex.org/I32574673","display_name":"Shantou University","ror":"https://ror.org/01a099706","country_code":"CN","type":"education","lineage":["https://openalex.org/I32574673"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Cheng Liu","raw_affiliation_strings":["Department of Computer Science, Shantou University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Shantou University","institution_ids":["https://openalex.org/I32574673"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070982537","display_name":"Si Wu","orcid":"https://orcid.org/0000-0003-4022-0852","observed_orcids":["https://orcid.org/0000-0003-4022-0852"]},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Si Wu","raw_affiliation_strings":["School of Computer Science and Engineering, South China University of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, South China University of Technology","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5014196059","display_name":"Hau\u2212San Wong","orcid":"https://orcid.org/0000-0002-1530-7529","observed_orcids":["https://orcid.org/0000-0002-1530-7529"]},"institutions":[{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"education","lineage":["https://openalex.org/I168719708"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Hau San Wong","raw_affiliation_strings":["Department of Computer Science, City University of Hong Kong"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, City University of Hong Kong","institution_ids":["https://openalex.org/I168719708"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.5863,"has_fulltext":true,"cited_by_count":12,"citation_normalized_percentile":{"value":0.7233562,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":88,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"3268","last_page":"3274"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.305400013923645,"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":0.305400013923645,"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/T10057","display_name":"Face and Expression Recognition","score":0.19920000433921814,"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/T10028","display_name":"Topic Modeling","score":0.10890000313520432,"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":0.9620000123977661},{"id":"https://openalex.org/keywords/representation-learning","display_name":"representation learning","score":0.9909999966621399},{"id":"https://openalex.org/keywords/data-interpolation","display_name":"data interpolation","score":0.8349999785423279},{"id":"https://openalex.org/keywords/multivariate-interpolation","display_name":"multivariate interpolation","score":0.9950000047683716},{"id":"https://openalex.org/keywords/latent-space-regularization","display_name":"latent space regularization","score":0.6050000190734863},{"id":"https://openalex.org/keywords/maximum-mean-discrepancy","display_name":"maximum mean discrepancy","score":0.8560000061988831},{"id":"https://openalex.org/keywords/generative-adversarial-networks","display_name":"generative adversarial networks","score":0.9319999814033508},{"id":"https://openalex.org/keywords/data-manifold","display_name":"data manifold","score":0.6430000066757202},{"id":"https://openalex.org/keywords/generative-models","display_name":"generative models","score":0.4880000054836273}],"concepts":[{"id":"https://openalex.org/C137800194","wikidata":"https://www.wikidata.org/wiki/Q11713455","display_name":"Interpolation (computer graphics)","level":3,"score":0.8334314823150635},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.6994985938072205},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6591116786003113},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.5852444171905518},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5631754994392395},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.4642195701599121},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.45428988337516785},{"id":"https://openalex.org/C171836373","wikidata":"https://www.wikidata.org/wiki/Q2266329","display_name":"Linear interpolation","level":3,"score":0.4267186224460602},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.35043397545814514},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2144211232662201},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.08813810348510742},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.24963/ijcai.2019/453","doi":"https://doi.org/10.24963/ijcai.2019/453","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2019/453","pdf_url":"https://www.ijcai.org/proceedings/2019/0453.pdf","source":{"id":"https://openalex.org/S4306419999","display_name":"International Joint Conference on Artificial Intelligence","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.24963/ijcai.2019/453","doi":"https://doi.org/10.24963/ijcai.2019/453","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2019/453","pdf_url":"https://www.ijcai.org/proceedings/2019/0453.pdf","source":{"id":"https://openalex.org/S4306419999","display_name":"International Joint Conference on Artificial Intelligence","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"sustainable_development_goals":[],"study_designs":[],"awards":[{"id":"https://openalex.org/G145909667","display_name":null,"funder_award_id":"11300715","funder_id":"https://openalex.org/F4320309893","funder_display_name":"City University of Hong Kong"},{"id":"https://openalex.org/G5033022664","display_name":null,"funder_award_id":"61502173","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5526867466","display_name":null,"funder_award_id":"U1611461","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5930723989","display_name":null,"funder_award_id":"7005055","funder_id":"https://openalex.org/F4320309893","funder_display_name":"City University of Hong Kong"}],"funders":[{"id":"https://openalex.org/F4320309893","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2965052260.pdf","grobid_xml":"https://content.openalex.org/works/W2965052260.grobid-xml"},"referenced_works_count":30,"referenced_works":["https://openalex.org/W1834627138","https://openalex.org/W1959608418","https://openalex.org/W2095705004","https://openalex.org/W2108598243","https://openalex.org/W2112796928","https://openalex.org/W2113952909","https://openalex.org/W2118858186","https://openalex.org/W2125865219","https://openalex.org/W2127218421","https://openalex.org/W2145094598","https://openalex.org/W2173520492","https://openalex.org/W2173649752","https://openalex.org/W2248620004","https://openalex.org/W2335728318","https://openalex.org/W2411541852","https://openalex.org/W2546066744","https://openalex.org/W2567627528","https://openalex.org/W2593814746","https://openalex.org/W2767375635","https://openalex.org/W2884980254","https://openalex.org/W2909751683","https://openalex.org/W2952034151","https://openalex.org/W2963746531","https://openalex.org/W2963799213","https://openalex.org/W2964167449","https://openalex.org/W3038022805","https://openalex.org/W3118608800","https://openalex.org/W4239072543","https://openalex.org/W4302343661","https://openalex.org/W4320013936"],"related_works":["https://openalex.org/W2884980254","https://openalex.org/W4210914762","https://openalex.org/W3171859874","https://openalex.org/W3094127791","https://openalex.org/W3047495882","https://openalex.org/W2948559147","https://openalex.org/W3027227991","https://openalex.org/W4403634841","https://openalex.org/W2907147851","https://openalex.org/W3049358913"],"abstract_inverted_index":{"Autoencoders":[0],"enjoy":[1],"a":[2,39,46,118],"remarkable":[3],"ability":[4],"to":[5,64,85,134,145],"learn":[6],"data":[7,17,47,70,90,114],"representations.":[8,102],"Research":[9],"on":[10,45,120,160,163],"autoencoders":[11,31,107],"shows":[12],"that":[13,154],"the":[14,21,50,67,82,87,110,113,124,138],"effectiveness":[15],"of":[16,23,37,52,69,89,100],"interpolation":[18,28,71,84,91,95],"can":[19],"reflect":[20],"performance":[22,159],"representation":[24,75,155],"learning.":[25],"However,":[26],"existing":[27],"methods":[29],"in":[30,77,108,123,137],"do":[32],"not":[33,57],"have":[34],"enough":[35],"capability":[36,88],"traversing":[38],"possible":[40],"region":[41],"between":[42],"two":[43],"datapoints":[44,133],"manifold,":[48],"and":[49,72,112,130],"distribution":[51],"interpolated":[53],"latent":[54,101,111,121],"representations":[55,122],"is":[56],"considered.To":[58],"address":[59],"these":[60],"issues,":[61],"we":[62,80,105],"aim":[63],"fully":[65],"exert":[66],"potential":[68],"further":[73],"improve":[74],"learning":[76,156],"autoencoders.":[78],"Specifically,":[79],"propose":[81],"multidimensional":[83],"increase":[86],"by":[92,116],"randomly":[93],"setting":[94],"coefficients":[96],"for":[97],"each":[98],"dimension":[99],"In":[103],"addition,":[104],"regularize":[106],"both":[109],"spaces":[115],"imposing":[117],"prior":[119],"Maximum":[125],"Mean":[126],"Discrepancy":[127],"(MMD)":[128],"framework":[129],"encouraging":[131],"generated":[132],"be":[135],"realistic":[136],"Generative":[139],"Adversarial":[140],"Network":[141],"(GAN)":[142],"framework.":[143],"Compared":[144],"representative":[146],"models,":[147],"our":[148],"proposed":[149],"model":[150],"has":[151],"empirically":[152],"shown":[153],"exhibits":[157],"better":[158],"downstream":[161],"tasks":[162],"multiple":[164],"benchmarks.":[165]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":1}],"updated_date":"2026-11-04T10:54:05.112534","created_date":"2019-08-13T00:00:00"}
