{"id":"https://openalex.org/W7123340748","doi":"https://doi.org/10.1109/cdc57313.2025.11312067","title":"Distributionally Robust Adversarial Attacks with Mirrored Loss","display_name":"Distributionally Robust Adversarial Attacks with Mirrored Loss","publication_year":2025,"publication_date":"2025-12-09","ids":{"openalex":"https://openalex.org/W7123340748","doi":"https://doi.org/10.1109/cdc57313.2025.11312067"},"language":null,"primary_location":{"id":"doi:10.1109/cdc57313.2025.11312067","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cdc57313.2025.11312067","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 64th Conference on Decision and Control (CDC)","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/A5092772245","display_name":"Andr\u00e9 Bertolace","orcid":null},"institutions":[{"id":"https://openalex.org/I40120149","display_name":"University of Oxford","ror":"https://ror.org/052gg0110","country_code":"GB","type":"education","lineage":["https://openalex.org/I40120149"]},{"id":"https://openalex.org/I4210146410","display_name":"Science Oxford","ror":"https://ror.org/04j8yhy50","country_code":"GB","type":"nonprofit","lineage":["https://openalex.org/I4210146410"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Andr\u00e9 Bertolace","raw_affiliation_strings":["University of Oxford,Department of Engineering Science,Oxford,U.K.,OX1 3PJ"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Oxford,Department of Engineering Science,Oxford,U.K.,OX1 3PJ","institution_ids":["https://openalex.org/I40120149","https://openalex.org/I4210146410"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025590360","display_name":"Konstantinos Gatsis","orcid":"https://orcid.org/0000-0002-0734-5445"},"institutions":[{"id":"https://openalex.org/I7863295","display_name":"Villanova University","ror":"https://ror.org/02g7kd627","country_code":"US","type":"education","lineage":["https://openalex.org/I7863295"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Konstantinos Gatsis","raw_affiliation_strings":["Villanova University,Electrical and Computer Engennering,Villanova,PA,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Villanova University,Electrical and Computer Engennering,Villanova,PA,USA","institution_ids":["https://openalex.org/I7863295"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5000801527","display_name":"Kostas Margellos","orcid":"https://orcid.org/0000-0001-8865-8568"},"institutions":[{"id":"https://openalex.org/I40120149","display_name":"University of Oxford","ror":"https://ror.org/052gg0110","country_code":"GB","type":"education","lineage":["https://openalex.org/I40120149"]},{"id":"https://openalex.org/I4210146410","display_name":"Science Oxford","ror":"https://ror.org/04j8yhy50","country_code":"GB","type":"nonprofit","lineage":["https://openalex.org/I4210146410"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Kostas Margellos","raw_affiliation_strings":["University of Oxford,Department of Engineering Science,Oxford,U.K.,OX1 3PJ"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Oxford,Department of Engineering Science,Oxford,U.K.,OX1 3PJ","institution_ids":["https://openalex.org/I40120149","https://openalex.org/I4210146410"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.79235722,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1526","last_page":"1531"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9945999979972839,"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":0.9945999979972839,"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/T10883","display_name":"Ethics and Social Impacts of AI","score":0.0013000000035390258,"subfield":{"id":"https://openalex.org/subfields/3311","display_name":"Safety Research"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.0006000000284984708,"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":0.8574000000953674},{"id":"https://openalex.org/keywords/mnist-database","display_name":"MNIST database","score":0.6251000165939331},{"id":"https://openalex.org/keywords/binary-number","display_name":"Binary number","score":0.5493999719619751},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.4952999949455261},{"id":"https://openalex.org/keywords/binary-classification","display_name":"Binary classification","score":0.44839999079704285},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.38519999384880066},{"id":"https://openalex.org/keywords/distortion","display_name":"Distortion (music)","score":0.3630000054836273},{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.3346000015735626}],"concepts":[{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.8574000000953674},{"id":"https://openalex.org/C190502265","wikidata":"https://www.wikidata.org/wiki/Q17069496","display_name":"MNIST database","level":3,"score":0.6251000165939331},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.603600025177002},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.5493999719619751},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.4952999949455261},{"id":"https://openalex.org/C66905080","wikidata":"https://www.wikidata.org/wiki/Q17005494","display_name":"Binary classification","level":3,"score":0.44839999079704285},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4187000095844269},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.38519999384880066},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3781000077724457},{"id":"https://openalex.org/C126780896","wikidata":"https://www.wikidata.org/wiki/Q899871","display_name":"Distortion (music)","level":4,"score":0.3630000054836273},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.3346000015735626},{"id":"https://openalex.org/C149441793","wikidata":"https://www.wikidata.org/wiki/Q200726","display_name":"Probability distribution","level":2,"score":0.3165000081062317},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.30469998717308044},{"id":"https://openalex.org/C2777634741","wikidata":"https://www.wikidata.org/wiki/Q768993","display_name":"Wasserstein metric","level":2,"score":0.30219998955726624},{"id":"https://openalex.org/C2780522230","wikidata":"https://www.wikidata.org/wiki/Q1140419","display_name":"Ambiguity","level":2,"score":0.29589998722076416},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.29319998621940613},{"id":"https://openalex.org/C157972887","wikidata":"https://www.wikidata.org/wiki/Q463359","display_name":"Convex optimization","level":3,"score":0.2904999852180481},{"id":"https://openalex.org/C205203396","wikidata":"https://www.wikidata.org/wiki/Q612143","display_name":"Bilinear interpolation","level":2,"score":0.2782000005245209},{"id":"https://openalex.org/C191795146","wikidata":"https://www.wikidata.org/wiki/Q3878446","display_name":"Norm (philosophy)","level":2,"score":0.273499995470047},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.27160000801086426},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2667999863624573},{"id":"https://openalex.org/C2779190172","wikidata":"https://www.wikidata.org/wiki/Q4913888","display_name":"Binary data","level":3,"score":0.26190000772476196},{"id":"https://openalex.org/C2776029896","wikidata":"https://www.wikidata.org/wiki/Q3935810","display_name":"Relaxation (psychology)","level":2,"score":0.25769999623298645},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2529999911785126},{"id":"https://openalex.org/C112680207","wikidata":"https://www.wikidata.org/wiki/Q714886","display_name":"Regular polygon","level":2,"score":0.25189998745918274}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cdc57313.2025.11312067","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cdc57313.2025.11312067","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 64th Conference on Decision and Control (CDC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.6570724844932556}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"We":[0,37],"approach":[1,120],"the":[2,20,66,89,112],"problems":[3],"of":[4,22,28,42,68],"constructing":[5],"adversarial":[6,13,49,99,127],"attacks":[7,100],"under":[8],"a":[9,26,31,40,47,58,70,122],"distributionally":[10],"robust,":[11],"data-driven":[12],"attack":[14,128],"to":[15,74],"binary":[16,53,134],"classification":[17,24],"by":[18,101],"minimizing":[19,69],"probability":[21],"accurate":[23],"as":[25,78],"proxy":[27],"maximizing":[29],"misclassification,":[30],"metric":[32],"we":[33,64,92],"term":[34],"mirrored":[35,71],"loss.":[36],"show":[38],"that":[39,55,94,118],"relaxation":[41],"this":[43],"reformulation":[44],"results":[45],"in":[46,111],"convex":[48],"problem":[50,60],"for":[51,57,83],"linear":[52],"classifiers,":[54],"allows":[56],"tractable":[59],"formulation.":[61],"In":[62],"addition,":[63],"extend":[65],"approach,":[67],"loss":[72],"function,":[73],"non-convex":[75,113],"settings,":[76],"such":[77],"Convolutional":[79],"Neural":[80],"Networks":[81],"(CNNs),":[82],"multi-class":[84],"classification.":[85,135],"Through":[86],"experiments":[87],"on":[88],"MNIST":[90],"dataset,":[91],"demonstrate":[93],"our":[95,119],"method":[96],"outperforms":[97],"other":[98],"achieving":[102],"higher":[103],"misclassification":[104],"rates":[105],"with":[106,130],"lower":[107],"data":[108],"distortion":[109],"even":[110],"case.":[114],"These":[115],"findings":[116],"suggest":[117],"provides":[121],"more":[123],"effective":[124],"and":[125],"efficient":[126],"framework,":[129],"potential":[131],"applications":[132],"beyond":[133]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-01-14T00:00:00"}