{"id":"https://openalex.org/W4312724357","doi":"https://doi.org/10.1109/ijcnn55064.2022.9892161","title":"GTAT: Adversarial Training with Generated Triplets","display_name":"GTAT: Adversarial Training with Generated Triplets","publication_year":2022,"publication_date":"2022-07-18","ids":{"openalex":"https://openalex.org/W4312724357","doi":"https://doi.org/10.1109/ijcnn55064.2022.9892161"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn55064.2022.9892161","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn55064.2022.9892161","pdf_url":null,"source":{"id":"https://openalex.org/S4363607707","display_name":"2022 International Joint Conference on Neural Networks (IJCNN)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"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":"2022 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/A5101451793","display_name":"Baoli Wang","orcid":"https://orcid.org/0000-0001-5057-2339"},"institutions":[{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]},{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Baoli Wang","raw_affiliation_strings":["Institute of Computing Technology, Chinese Academy of Sciences,Beijing,China","Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China","University of Chinese Academy of Sciences, China"],"affiliations":[{"raw_affiliation_string":"Institute of Computing Technology, Chinese Academy of Sciences,Beijing,China","institution_ids":["https://openalex.org/I4210090176","https://openalex.org/I19820366"]},{"raw_affiliation_string":"Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210090176","https://openalex.org/I19820366"]},{"raw_affiliation_string":"University of Chinese Academy of Sciences, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046658556","display_name":"Xinxin Fan","orcid":"https://orcid.org/0000-0002-6659-7431"},"institutions":[{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]},{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinxin Fan","raw_affiliation_strings":["Institute of Computing Technology, Chinese Academy of Sciences,Beijing,China","Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Institute of Computing Technology, Chinese Academy of Sciences,Beijing,China","institution_ids":["https://openalex.org/I4210090176","https://openalex.org/I19820366"]},{"raw_affiliation_string":"Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210090176","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009094383","display_name":"Quanliang Jing","orcid":"https://orcid.org/0000-0002-7670-7729"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]},{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Quanliang Jing","raw_affiliation_strings":["Institute of Computing Technology, Chinese Academy of Sciences,Beijing,China","Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China","University of Chinese Academy of Sciences, China"],"affiliations":[{"raw_affiliation_string":"Institute of Computing Technology, Chinese Academy of Sciences,Beijing,China","institution_ids":["https://openalex.org/I4210090176","https://openalex.org/I19820366"]},{"raw_affiliation_string":"Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210090176","https://openalex.org/I19820366"]},{"raw_affiliation_string":"University of Chinese Academy of Sciences, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050314527","display_name":"Yueyang Su","orcid":"https://orcid.org/0000-0002-6154-8059"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]},{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]},{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yueyang Su","raw_affiliation_strings":["Institute of Computing Technology, Chinese Academy of Sciences,Beijing,China","Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China","University of Chinese Academy of Sciences, China"],"affiliations":[{"raw_affiliation_string":"Institute of Computing Technology, Chinese Academy of Sciences,Beijing,China","institution_ids":["https://openalex.org/I4210090176","https://openalex.org/I19820366"]},{"raw_affiliation_string":"Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210090176","https://openalex.org/I19820366"]},{"raw_affiliation_string":"University of Chinese Academy of Sciences, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100416946","display_name":"Jingwei Li","orcid":"https://orcid.org/0000-0003-0143-7338"},"institutions":[{"id":"https://openalex.org/I63190737","display_name":"University at Buffalo, State University of New York","ror":"https://ror.org/01y64my43","country_code":"US","type":"education","lineage":["https://openalex.org/I63190737"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jingwei Li","raw_affiliation_strings":["University of Buffalo,Department of Computer Science and Engineerting,SUNY,US","Department of Computer Science and Engineerting, University of Buffalo, SUNY, US"],"affiliations":[{"raw_affiliation_string":"University of Buffalo,Department of Computer Science and Engineerting,SUNY,US","institution_ids":["https://openalex.org/I63190737"]},{"raw_affiliation_string":"Department of Computer Science and Engineerting, University of Buffalo, SUNY, US","institution_ids":["https://openalex.org/I63190737"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102995513","display_name":"Jingping Bi","orcid":"https://orcid.org/0000-0001-7858-4980"},"institutions":[{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]},{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingping Bi","raw_affiliation_strings":["Institute of Computing Technology, Chinese Academy of Sciences,Beijing,China","Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Institute of Computing Technology, Chinese Academy of Sciences,Beijing,China","institution_ids":["https://openalex.org/I4210090176","https://openalex.org/I19820366"]},{"raw_affiliation_string":"Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210090176","https://openalex.org/I19820366"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5101451793"],"corresponding_institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210090176","https://openalex.org/I4210165038"],"apc_list":null,"apc_paid":null,"fwci":0.1039,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.3262228,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9991999864578247,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9991999864578247,"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/adversarial-system","display_name":"Adversarial system","score":0.9402315616607666},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6949033141136169},{"id":"https://openalex.org/keywords/generator","display_name":"Generator (circuit theory)","score":0.6549085378646851},{"id":"https://openalex.org/keywords/mnist-database","display_name":"MNIST database","score":0.6434831023216248},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.6041795611381531},{"id":"https://openalex.org/keywords/constraint","display_name":"Constraint (computer-aided design)","score":0.5853865742683411},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5667638182640076},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.541414737701416},{"id":"https://openalex.org/keywords/retraining","display_name":"Retraining","score":0.4185653328895569},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3315626382827759},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.22675821185112},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.16492187976837158},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1604352593421936},{"id":"https://openalex.org/keywords/law","display_name":"Law","score":0.06577056646347046}],"concepts":[{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.9402315616607666},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6949033141136169},{"id":"https://openalex.org/C2780992000","wikidata":"https://www.wikidata.org/wiki/Q17016113","display_name":"Generator (circuit theory)","level":3,"score":0.6549085378646851},{"id":"https://openalex.org/C190502265","wikidata":"https://www.wikidata.org/wiki/Q17069496","display_name":"MNIST database","level":3,"score":0.6434831023216248},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.6041795611381531},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.5853865742683411},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5667638182640076},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.541414737701416},{"id":"https://openalex.org/C2778712577","wikidata":"https://www.wikidata.org/wiki/Q3505966","display_name":"Retraining","level":2,"score":0.4185653328895569},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3315626382827759},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.22675821185112},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.16492187976837158},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1604352593421936},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.06577056646347046},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn55064.2022.9892161","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn55064.2022.9892161","pdf_url":null,"source":{"id":"https://openalex.org/S4363607707","display_name":"2022 International Joint Conference on Neural Networks (IJCNN)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"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":"2022 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","score":0.46000000834465027,"display_name":"Industry, innovation and infrastructure"}],"awards":[{"id":"https://openalex.org/G6944053612","display_name":null,"funder_award_id":"62077044,61702470,62002343","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"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W1673923490","https://openalex.org/W1932198206","https://openalex.org/W1945616565","https://openalex.org/W2096733369","https://openalex.org/W2100799972","https://openalex.org/W2603766943","https://openalex.org/W2620038827","https://openalex.org/W2759358869","https://openalex.org/W2774644650","https://openalex.org/W2791953061","https://openalex.org/W2895115565","https://openalex.org/W2962872506","https://openalex.org/W2963143631","https://openalex.org/W2963542245","https://openalex.org/W2963744840","https://openalex.org/W2963771536","https://openalex.org/W2963855547","https://openalex.org/W2963857521","https://openalex.org/W2964082701","https://openalex.org/W2965154261","https://openalex.org/W2972267366","https://openalex.org/W2979450790","https://openalex.org/W2981597369","https://openalex.org/W3015720943","https://openalex.org/W3035032188","https://openalex.org/W3199421976","https://openalex.org/W4245534220","https://openalex.org/W4293846201","https://openalex.org/W4300725094","https://openalex.org/W6637162671","https://openalex.org/W6640425456","https://openalex.org/W6719080892","https://openalex.org/W6725195833","https://openalex.org/W6739868092","https://openalex.org/W6744817461","https://openalex.org/W6748475379","https://openalex.org/W6748965907","https://openalex.org/W6767248609","https://openalex.org/W6774681163"],"related_works":["https://openalex.org/W4386603768","https://openalex.org/W2950475743","https://openalex.org/W2886711096","https://openalex.org/W2750384547","https://openalex.org/W4380078352","https://openalex.org/W3046591097","https://openalex.org/W4389249638","https://openalex.org/W2733410219","https://openalex.org/W2734358244","https://openalex.org/W4388700941"],"abstract_inverted_index":{"To":[0],"circumvent":[1],"the":[2,40,58,71,82,94,103,128,150,160],"grave":[3],"problem":[4],"of":[5,12,50,135,145],"present":[6],"adversarial":[7,23,45,118,129,140,152,162],"training":[8,24,119,130,141],"methods,":[9],"i.e.":[10],"distortion":[11],"classification":[13,59,95],"surface,":[14],"we":[15],"in":[16,26],"this":[17,48],"paper":[18],"propose":[19],"a":[20,28,31,125,132],"generated":[21,51,151,161],"Triplet-based":[22],"method-GTAT,":[25],"which":[27],"Generator":[29],"generates":[30],"semi-hard":[32,52,138],"Triplet":[33,53],"by":[34],"design,":[35],"rather":[36],"than":[37],"directly":[38],"invoking":[39],"existing":[41,155],"clean":[42,156],"examples":[43,73,84,153,163],"and":[44,78,92,106,154],"examples.":[46],"Through":[47],"kind":[49],"constraint,":[54],"GTAT":[55,113,123],"can":[56],"reshape":[57],"boundaries":[60],"appropriately":[61],"across":[62,97],"various":[63],"classes,":[64],"arising":[65],"from":[66,131],"two-facet":[67],"synergies:":[68],"i)":[69],"pull":[70],"intra-class":[72],"together":[74],"with":[75,85],"tight":[76],"distances;":[77],"ii)":[79],"push":[80],"away":[81],"inter-class":[83],"broad":[86],"distances.":[87],"This":[88],"synergy":[89],"will":[90],"simplify":[91],"broaden":[93],"surfaces":[96],"different":[98],"classes.":[99],"Extensive":[100],"experiments":[101],"on":[102,149,159],"popular":[104],"MNIST":[105],"CIFAR-10":[107],"datasets":[108],"show":[109],"that":[110],"our":[111],"proposed":[112],"significantly":[114],"outperforms":[115],"other":[116],"state-of-the-art":[117],"methods.":[120],"We":[121],"believe":[122],"opens":[124],"door":[126],"for":[127],"new":[133],"horizon":[134],"rationally":[136],"generating":[137],"Triplet-satisfied":[139],"(retraining)":[142],"examples,":[143,157],"instead":[144],"straightly":[146],"performing":[147],"retraining":[148],"or":[158],"only.":[164]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}