{"id":"https://openalex.org/W3129826583","doi":null,"title":"Sparta: Spatially Attentive and Adversarially Robust Activations","display_name":"Sparta: Spatially Attentive and Adversarially Robust Activations","publication_year":2021,"publication_date":"2021-05-04","ids":{"openalex":"https://openalex.org/W3129826583","mag":"3129826583"},"language":"en","primary_location":{"id":"mag:3129826583","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/pdf/2105.08269.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},"volume":null,"type":"preprint","is_traditional":true,"indexed_in":[],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2105.08269.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5026239594","display_name":"Qing Guo","orcid":"https://orcid.org/0000-0003-0974-9299","observed_orcids":["https://orcid.org/0000-0003-0974-9299","https://orcid.org/0009-0004-4395-9163"]},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Qing Guo","raw_affiliation_strings":["Nanyang Technological Univ"],"raw_orcid":"https://orcid.org/0000-0003-0974-9299","affiliations":[{"raw_affiliation_string":"Nanyang Technological Univ","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034751153","display_name":"Felix Juefei-Xu","orcid":"https://orcid.org/0000-0002-0857-8611","observed_orcids":["https://orcid.org/0000-0002-0857-8611"]},"institutions":[{"id":"https://openalex.org/I4210095624","display_name":"Alibaba Group (United States)","ror":"https://ror.org/00rn0m335","country_code":"US","type":"company","lineage":["https://openalex.org/I4210095624","https://openalex.org/I45928872"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Felix Juefei-Xu","raw_affiliation_strings":["Alibaba Group,USA"],"raw_orcid":"https://orcid.org/0000-0002-0857-8611","affiliations":[{"raw_affiliation_string":"Alibaba Group,USA","institution_ids":["https://openalex.org/I4210095624"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5106665107","display_name":"Changqing Zhou","orcid":"https://orcid.org/0000-0002-7269-6380","observed_orcids":["https://orcid.org/0000-0002-7269-6380"]},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Changqing Zhou","raw_affiliation_strings":["Nanyang Technological Univ"],"raw_orcid":"https://orcid.org/0000-0002-7269-6380","affiliations":[{"raw_affiliation_string":"Nanyang Technological Univ","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101468661","display_name":"Lei Ma","orcid":"https://orcid.org/0000-0002-8621-2420","observed_orcids":["https://orcid.org/0000-0002-8621-2420"]},"institutions":[{"id":"https://openalex.org/I135598925","display_name":"Kyushu University","ror":"https://ror.org/00p4k0j84","country_code":"JP","type":"education","lineage":["https://openalex.org/I135598925"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Lei Ma","raw_affiliation_strings":["Kyushu University"],"raw_orcid":"https://orcid.org/0000-0002-8621-2420","affiliations":[{"raw_affiliation_string":"Kyushu University","institution_ids":["https://openalex.org/I135598925"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084396416","display_name":"Xiaofei Xie","orcid":"https://orcid.org/0000-0002-1288-6502","observed_orcids":["https://orcid.org/0000-0002-1288-6502"]},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Xiaofei Xie","raw_affiliation_strings":["Nanyang Technological Univ"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanyang Technological Univ","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100721881","display_name":"Wei Feng","orcid":"https://orcid.org/0000-0003-3809-1086","observed_orcids":["https://orcid.org/0000-0003-3809-1086"]},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Feng","raw_affiliation_strings":["Tianjin University"],"raw_orcid":"https://orcid.org/0000-0003-3809-1086","affiliations":[{"raw_affiliation_string":"Tianjin University","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100355692","display_name":"Yang Liu","orcid":"https://orcid.org/0000-0001-7300-9215","observed_orcids":["https://orcid.org/0000-0001-7300-9215","https://orcid.org/0000-0002-6276-1468","https://orcid.org/0000-0001-9704-8120","https://orcid.org/0009-0003-6607-861X"]},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Yang Liu","raw_affiliation_strings":["Nanyang Technological Univ"],"raw_orcid":"https://orcid.org/0000-0001-7300-9215","affiliations":[{"raw_affiliation_string":"Nanyang Technological Univ","institution_ids":["https://openalex.org/I172675005"]}]}],"institutions":[],"countries_distinct_count":4,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9994999766349792,"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":0.9994999766349792,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.0,"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/T11424","display_name":"Security and Verification in Computing","score":0.0,"subfield":{"id":"https://openalex.org/subfields/1708","display_name":"Hardware and Architecture"},"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-robustness","display_name":"adversarial robustness","score":0.8579999804496765},{"id":"https://openalex.org/keywords/activation-functions","display_name":"activation functions","score":0.824999988079071},{"id":"https://openalex.org/keywords/relu","display_name":"ReLU","score":0.6990000009536743},{"id":"https://openalex.org/keywords/adversarial-training","display_name":"adversarial training","score":0.953000009059906},{"id":"https://openalex.org/keywords/white-box-attacks","display_name":"white-box attacks","score":0.8270000219345093},{"id":"https://openalex.org/keywords/swish","display_name":"Swish","score":0.9279999732971191},{"id":"https://openalex.org/keywords/feature-denoising","display_name":"feature denoising","score":0.8930000066757202},{"id":"https://openalex.org/keywords/deep-neural-network","display_name":"deep neural network","score":0.6069999933242798}],"concepts":[{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.8617420196533203},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7398815155029297},{"id":"https://openalex.org/C61272859","wikidata":"https://www.wikidata.org/wiki/Q7834031","display_name":"Transferability","level":3,"score":0.7107568979263306},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.6813732385635376},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.6321908235549927},{"id":"https://openalex.org/C38365724","wikidata":"https://www.wikidata.org/wiki/Q4677469","display_name":"Activation function","level":3,"score":0.5611029863357544},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5344613790512085},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.5177366137504578},{"id":"https://openalex.org/C40969351","wikidata":"https://www.wikidata.org/wiki/Q3516228","display_name":"Word error rate","level":2,"score":0.509638786315918},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.43402761220932007},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.41564545035362244},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.40748512744903564},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3686671555042267},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C140331021","wikidata":"https://www.wikidata.org/wiki/Q1868104","display_name":"Logit","level":2,"score":0.0},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","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/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"mag:3129826583","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/pdf/2105.08269.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null}],"best_oa_location":{"id":"mag:3129826583","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/pdf/2105.08269.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":43,"referenced_works":["https://openalex.org/W1533861849","https://openalex.org/W1665214252","https://openalex.org/W1677182931","https://openalex.org/W2156387975","https://openalex.org/W2163605009","https://openalex.org/W2174868984","https://openalex.org/W2176412452","https://openalex.org/W2194775991","https://openalex.org/W2279458746","https://openalex.org/W2294059674","https://openalex.org/W2335728318","https://openalex.org/W2462831000","https://openalex.org/W2610190180","https://openalex.org/W2618235498","https://openalex.org/W2620038827","https://openalex.org/W2747237166","https://openalex.org/W2765233338","https://openalex.org/W2765384636","https://openalex.org/W2767286248","https://openalex.org/W2767962654","https://openalex.org/W2774018344","https://openalex.org/W2783692467","https://openalex.org/W2785269845","https://openalex.org/W2786118190","https://openalex.org/W2787496614","https://openalex.org/W2787708942","https://openalex.org/W2787733970","https://openalex.org/W2791953061","https://openalex.org/W2892090366","https://openalex.org/W2899663614","https://openalex.org/W2900578291","https://openalex.org/W2962710014","https://openalex.org/W2962872506","https://openalex.org/W2963207607","https://openalex.org/W2963420686","https://openalex.org/W2964153729","https://openalex.org/W2964253222","https://openalex.org/W2970682262","https://openalex.org/W3034421924","https://openalex.org/W3035084548","https://openalex.org/W3037742886","https://openalex.org/W3118608800","https://openalex.org/W4407638561"],"related_works":["https://openalex.org/W4310815564","https://openalex.org/W3037742886","https://openalex.org/W7213539077","https://openalex.org/W2952068767","https://openalex.org/W6948049804","https://openalex.org/W3034834795","https://openalex.org/W2890918255","https://openalex.org/W3048203754","https://openalex.org/W6940392091","https://openalex.org/W2907912810"],"abstract_inverted_index":{"Adversarial":[0],"training":[1,35,73,76],"has":[2,41],"been":[3,43],"demonstrated":[4,165],"to":[5,33,79,104,190,226],"be":[6,188,224],"useful":[7],"for":[8,31,182],"improving":[9],"the":[10,18,26,58,65,68,125,129,136,142,156,202,252],"robustness":[11,107,200,240],"of":[12,20,64,158,169,256],"deep":[13],"neural":[14],"networks":[15],"(DNNs).":[16],"However,":[17],"impacts":[19],"basic":[21],"network":[22],"components":[23],"(e.g.,":[24,185,196,221,234],"ReLU,":[25],"widely":[27],"used":[28],"activation":[29,91,131,145],"function":[30,181,216],"DNNs)":[32],"adversarial":[34,75,81,113],"effectiveness":[36],"received":[37],"less":[38,77],"attention":[39],"and":[40,60,74,97,115,141,149,236,254],"not":[42],"comprehensively":[44],"investigated":[45],"so":[46],"far.":[47],"To":[48,83],"fill":[49],"this":[50,53],"gap,":[51],"in":[52],"work,":[54],"we":[55,87],"argue":[56],"that":[57],"spatially-shared":[59],"input-independent":[61],"activating":[62],"properties":[63,168,249],"ReLU":[66,206,245],"make":[67],"DNNs":[69,103,126,230,242],"under":[70],"both":[71],"standard":[72],"robust":[78,194,229],"white-box":[80],"attacks.":[82],"address":[84],"such":[85],"challenges,":[86],"design":[88],"a":[89],"novel":[90],"function,":[92,146],"i.e.,":[93,147],"Sparta:":[94],"Spatially":[95],"Attentive":[96],"Adversarially":[98],"Robust":[99],"Activation,":[100],"which":[101],"enables":[102],"achieve":[105,238],"higher":[106,199,239],"(i.e.,":[108,117],"lower":[109,118],"error":[110,119],"rate":[111,120],"on":[112,121,128,218,231],"examples)":[114,123],"accuracy":[116],"clean":[122],"than":[124,201,241],"based":[127],"state-of-the-art":[130,143],"functions.":[132],"We":[133],"further":[134],"investigate":[135],"relationships":[137],"between":[138],"our":[139,159,170],"Sparta":[140,180,215],"search-based":[144],"Swish,":[148],"feature":[150],"denoising":[151],"method,":[152],"providing":[153],"insights":[154],"about":[155],"advantages":[157],"method.":[160],"Moreover,":[161],"comprehensive":[162],"evaluations":[163],"have":[164,250],"two":[166],"important":[167],"method:":[171],"First,":[172],"superior":[173,210],"transferability":[174,211],"across":[175,212],"DNNs.":[176],"Our":[177],"adversarially":[178,193,228],"trained":[179,217],"one":[183,203,219],"DNN":[184,195],"ResNet-18)":[186],"can":[187,223],"fixed":[189],"train":[191,227],"another":[192,232],"ResNet-34),":[197],"achieving":[198],"using":[204],"vanilla":[205,244],"as":[207,246],"activation.":[208,247],"Second,":[209],"datasets.":[213],"The":[214],"dataset":[220,233],"CIFAR-10)":[222],"employed":[225],"SVHN)":[235],"helps":[237],"with":[243],"These":[248],"highlighted":[251],"flexibility":[253],"versatility":[255],"Sparta.":[257],"Accompanying":[258],"code":[259],"is":[260],"also":[261],"submitted.":[262]},"counts_by_year":[],"updated_date":"2026-10-29T09:56:32.521200","created_date":"2021-03-01T00:00:00"}