{"id":"https://openalex.org/W4392910567","doi":"https://doi.org/10.1109/icassp48485.2024.10446884","title":"DeepGRE: Global Robustness Evaluation of Deep Neural Networks","display_name":"DeepGRE: Global Robustness Evaluation of Deep Neural Networks","publication_year":2024,"publication_date":"2024-03-18","ids":{"openalex":"https://openalex.org/W4392910567","doi":"https://doi.org/10.1109/icassp48485.2024.10446884"},"language":"en","primary_location":{"id":"doi:10.1109/icassp48485.2024.10446884","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icassp48485.2024.10446884","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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/A5059107732","display_name":"Tianle Zhang","orcid":"https://orcid.org/0000-0003-4881-2406"},"institutions":[{"id":"https://openalex.org/I146655781","display_name":"University of Liverpool","ror":"https://ror.org/04xs57h96","country_code":"GB","type":"education","lineage":["https://openalex.org/I146655781"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Tianle Zhang","raw_affiliation_strings":["University of Liverpool,UK","University of Liverpool, UK"],"affiliations":[{"raw_affiliation_string":"University of Liverpool,UK","institution_ids":["https://openalex.org/I146655781"]},{"raw_affiliation_string":"University of Liverpool, UK","institution_ids":["https://openalex.org/I146655781"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038889450","display_name":"Jiaxu Liu","orcid":"https://orcid.org/0000-0003-0815-3979"},"institutions":[{"id":"https://openalex.org/I146655781","display_name":"University of Liverpool","ror":"https://ror.org/04xs57h96","country_code":"GB","type":"education","lineage":["https://openalex.org/I146655781"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Jiaxu Liu","raw_affiliation_strings":["University of Liverpool,UK","University of Liverpool, UK"],"affiliations":[{"raw_affiliation_string":"University of Liverpool,UK","institution_ids":["https://openalex.org/I146655781"]},{"raw_affiliation_string":"University of Liverpool, UK","institution_ids":["https://openalex.org/I146655781"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081956313","display_name":"Yanghao Zhang","orcid":"https://orcid.org/0000-0002-8499-0974"},"institutions":[{"id":"https://openalex.org/I146655781","display_name":"University of Liverpool","ror":"https://ror.org/04xs57h96","country_code":"GB","type":"education","lineage":["https://openalex.org/I146655781"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Yanghao Zhang","raw_affiliation_strings":["University of Liverpool,UK","University of Liverpool, UK"],"affiliations":[{"raw_affiliation_string":"University of Liverpool,UK","institution_ids":["https://openalex.org/I146655781"]},{"raw_affiliation_string":"University of Liverpool, UK","institution_ids":["https://openalex.org/I146655781"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054272337","display_name":"Ronghui Mu","orcid":null},"institutions":[{"id":"https://openalex.org/I146655781","display_name":"University of Liverpool","ror":"https://ror.org/04xs57h96","country_code":"GB","type":"education","lineage":["https://openalex.org/I146655781"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Ronghui Mu","raw_affiliation_strings":["University of Liverpool,UK","University of Liverpool, UK"],"affiliations":[{"raw_affiliation_string":"University of Liverpool,UK","institution_ids":["https://openalex.org/I146655781"]},{"raw_affiliation_string":"University of Liverpool, UK","institution_ids":["https://openalex.org/I146655781"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5074225885","display_name":"Wenjie Ruan","orcid":"https://orcid.org/0000-0002-8311-8738"},"institutions":[{"id":"https://openalex.org/I146655781","display_name":"University of Liverpool","ror":"https://ror.org/04xs57h96","country_code":"GB","type":"education","lineage":["https://openalex.org/I146655781"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Wenjie Ruan","raw_affiliation_strings":["University of Liverpool,UK","University of Liverpool, UK"],"affiliations":[{"raw_affiliation_string":"University of Liverpool,UK","institution_ids":["https://openalex.org/I146655781"]},{"raw_affiliation_string":"University of Liverpool, UK","institution_ids":["https://openalex.org/I146655781"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5059107732"],"corresponding_institution_ids":["https://openalex.org/I146655781"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.02846329,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"6990","last_page":"6994"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10876","display_name":"Fault Detection and Control Systems","score":0.8744999766349792,"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"}},"topics":[{"id":"https://openalex.org/T10876","display_name":"Fault Detection and Control Systems","score":0.8744999766349792,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.8550999760627747,"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/T10320","display_name":"Neural Networks and Applications","score":0.785099983215332,"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/robustness","display_name":"Robustness (evolution)","score":0.7996857762336731},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6933924555778503},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6247195601463318},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.48280346393585205},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4656525254249573}],"concepts":[{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7996857762336731},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6933924555778503},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6247195601463318},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.48280346393585205},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4656525254249573},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","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},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp48485.2024.10446884","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icassp48485.2024.10446884","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W1533955387","https://openalex.org/W2144906988","https://openalex.org/W2760733685","https://openalex.org/W2800473699","https://openalex.org/W2897320933","https://openalex.org/W2955566917","https://openalex.org/W2963857521","https://openalex.org/W3036286896","https://openalex.org/W3111818035","https://openalex.org/W4284967541","https://openalex.org/W4287637349","https://openalex.org/W4298162466","https://openalex.org/W4320013936","https://openalex.org/W4327652727","https://openalex.org/W4366732104","https://openalex.org/W4375868996","https://openalex.org/W6637162671","https://openalex.org/W6729756640","https://openalex.org/W6745094425","https://openalex.org/W6748458661","https://openalex.org/W6748582592","https://openalex.org/W6752378368","https://openalex.org/W6755312952","https://openalex.org/W6760909513","https://openalex.org/W6774469542","https://openalex.org/W6784493056","https://openalex.org/W6788762440","https://openalex.org/W6790764942","https://openalex.org/W6838975948","https://openalex.org/W6839045361"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W4379116102","https://openalex.org/W3210882018","https://openalex.org/W2970990331","https://openalex.org/W3207178610","https://openalex.org/W3211782752","https://openalex.org/W4309864825"],"abstract_inverted_index":{"Robustness":[0],"measurements":[1],"on":[2,149,158],"deep":[3],"neural":[4],"networks":[5],"(DNNs)":[6],"have":[7,17],"gained":[8],"significant":[9],"attention,":[10],"especially":[11],"in":[12,83],"safety-critical":[13],"applications.":[14],"Numerous":[15],"studies":[16],"been":[18],"devoted":[19],"to":[20,100],"assessing":[21],"the":[22,43,53,58,110,159],"robustness":[23,29,56,78,91,105,143,147],"of":[24,34,52,80,103],"classifiers":[25],"by":[26,121],"averaging":[27],"local":[28,44,90],"over":[30,57],"a":[31,39,71,126,130,155],"fixed":[32],"set":[33],"data":[35,62],"samples,":[36],"such":[37],"as":[38],"test":[40],"set.":[41],"However,":[42],"statistics":[45],"may":[46],"not":[47],"provide":[48],"an":[49,137],"accurate":[50],"representation":[51],"actual":[54],"global":[55,77,104,142,146],"entire":[59],"underlying":[60],"unknown":[61],"distribution.":[63],"To":[64],"address":[65],"this":[66,68,133],"challenge,":[67],"paper":[69],"proposes":[70],"novel":[72],"framework,":[73],"namely":[74],"DeepGRE,":[75],"for":[76,166],"estimates":[79,102,165],"adversarial":[81],"perturbation":[82],"combination":[84],"with":[85,106],"generative":[86,127],"models":[87],"and":[88,114,144,163],"existing":[89],"evaluation":[92],"methods.":[93],"Besides,":[94],"DeepGRE":[95],"employs":[96],"Quasi-Monte":[97],"Carlo":[98],"approach":[99],"produce":[101],"low":[107],"variance,":[108],"making":[109],"assessments":[111],"more":[112],"reliable":[113],"statistically":[115],"sound,":[116],"since":[117],"randomness":[118],"is":[119,171],"introduced":[120],"all":[122],"samples":[123],"drawn":[124],"from":[125],"model.":[128],"From":[129],"theoretical":[131],"perspective,":[132],"work":[134],"naturally":[135],"provides":[136],"upper":[138],"bound":[139],"between":[140,161],"true":[141,162],"estimated":[145],"based":[148],"Lipschitz":[150],"continuity.":[151],"Also,":[152],"it":[153],"derives":[154],"statistical":[156],"guarantee":[157],"difference":[160],"empirical":[164],"sample":[167],"complexity.":[168],"Our":[169],"code":[170],"available":[172],"at":[173],"https://github.com/TrustAI/DeepGRE.":[174]},"counts_by_year":[],"updated_date":"2025-12-25T23:11:45.687758","created_date":"2025-10-10T00:00:00"}