{"id":"https://openalex.org/W2978447704","doi":"https://doi.org/10.1109/ijcnn.2019.8852298","title":"Learning Adaptive Weight Masking for Adversarial Examples","display_name":"Learning Adaptive Weight Masking for Adversarial Examples","publication_year":2019,"publication_date":"2019-07-01","ids":{"openalex":"https://openalex.org/W2978447704","doi":"https://doi.org/10.1109/ijcnn.2019.8852298","mag":"2978447704"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2019.8852298","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2019.8852298","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 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/A5017547658","display_name":"Yoshimasa Kubo","orcid":null},"institutions":[{"id":"https://openalex.org/I129902397","display_name":"Dalhousie University","ror":"https://ror.org/01e6qks80","country_code":"CA","type":"education","lineage":["https://openalex.org/I129902397"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Yoshimasa Kubo","raw_affiliation_strings":["Faculty of Computer Science, Dalhousie University, Halifax, Canada"],"affiliations":[{"raw_affiliation_string":"Faculty of Computer Science, Dalhousie University, Halifax, Canada","institution_ids":["https://openalex.org/I129902397"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023021291","display_name":"Michael D. Traynor","orcid":"https://orcid.org/0000-0001-6779-9273"},"institutions":[{"id":"https://openalex.org/I129902397","display_name":"Dalhousie University","ror":"https://ror.org/01e6qks80","country_code":"CA","type":"education","lineage":["https://openalex.org/I129902397"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Michael Traynor","raw_affiliation_strings":["Faculty of Computer Science, Dalhousie University, Halifax, Canada"],"affiliations":[{"raw_affiliation_string":"Faculty of Computer Science, Dalhousie University, Halifax, Canada","institution_ids":["https://openalex.org/I129902397"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088920905","display_name":"Thomas Trappenberg","orcid":"https://orcid.org/0000-0002-6144-8963"},"institutions":[{"id":"https://openalex.org/I129902397","display_name":"Dalhousie University","ror":"https://ror.org/01e6qks80","country_code":"CA","type":"education","lineage":["https://openalex.org/I129902397"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Thomas Trappenberg","raw_affiliation_strings":["Faculty of Computer Science, Dalhousie University, Halifax, Canada"],"affiliations":[{"raw_affiliation_string":"Faculty of Computer Science, Dalhousie University, Halifax, Canada","institution_ids":["https://openalex.org/I129902397"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5082789942","display_name":"Sageev Oore","orcid":"https://orcid.org/0000-0002-8130-3569"},"institutions":[{"id":"https://openalex.org/I129902397","display_name":"Dalhousie University","ror":"https://ror.org/01e6qks80","country_code":"CA","type":"education","lineage":["https://openalex.org/I129902397"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Sageev Oore","raw_affiliation_strings":["Faculty of Computer Science, Dalhousie University, Halifax, Canada"],"affiliations":[{"raw_affiliation_string":"Faculty of Computer Science, Dalhousie University, Halifax, Canada","institution_ids":["https://openalex.org/I129902397"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5017547658"],"corresponding_institution_ids":["https://openalex.org/I129902397"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.11719794,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"28","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":1.0,"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":1.0,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9958999752998352,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9891999959945679,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7379348278045654},{"id":"https://openalex.org/keywords/sigmoid-function","display_name":"Sigmoid function","score":0.6894546747207642},{"id":"https://openalex.org/keywords/pointwise","display_name":"Pointwise","score":0.6350805759429932},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5960766077041626},{"id":"https://openalex.org/keywords/masking","display_name":"Masking (illustration)","score":0.5928021669387817},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5502866506576538},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5125131607055664},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4683118760585785},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.44562917947769165},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.4180077016353607},{"id":"https://openalex.org/keywords/layer","display_name":"Layer (electronics)","score":0.41689634323120117},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.37480634450912476},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.20617201924324036}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7379348278045654},{"id":"https://openalex.org/C81388566","wikidata":"https://www.wikidata.org/wiki/Q526668","display_name":"Sigmoid function","level":3,"score":0.6894546747207642},{"id":"https://openalex.org/C2777984123","wikidata":"https://www.wikidata.org/wiki/Q9248237","display_name":"Pointwise","level":2,"score":0.6350805759429932},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5960766077041626},{"id":"https://openalex.org/C2777402240","wikidata":"https://www.wikidata.org/wiki/Q6783436","display_name":"Masking (illustration)","level":2,"score":0.5928021669387817},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5502866506576538},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5125131607055664},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4683118760585785},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.44562917947769165},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.4180077016353607},{"id":"https://openalex.org/C2779227376","wikidata":"https://www.wikidata.org/wiki/Q6505497","display_name":"Layer (electronics)","level":2,"score":0.41689634323120117},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.37480634450912476},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.20617201924324036},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn.2019.8852298","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2019.8852298","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":52,"referenced_works":["https://openalex.org/W4919037","https://openalex.org/W1522301498","https://openalex.org/W1673923490","https://openalex.org/W1826234144","https://openalex.org/W1836465849","https://openalex.org/W1902934009","https://openalex.org/W1924770834","https://openalex.org/W1945616565","https://openalex.org/W2064675550","https://openalex.org/W2136836265","https://openalex.org/W2242818861","https://openalex.org/W2460937040","https://openalex.org/W2510842514","https://openalex.org/W2519091744","https://openalex.org/W2551895583","https://openalex.org/W2785335295","https://openalex.org/W2804230133","https://openalex.org/W2892090366","https://openalex.org/W2949382160","https://openalex.org/W2951595529","https://openalex.org/W2962699575","https://openalex.org/W2963207607","https://openalex.org/W2963389226","https://openalex.org/W2963735467","https://openalex.org/W2964121744","https://openalex.org/W2964153729","https://openalex.org/W3100646226","https://openalex.org/W3118608800","https://openalex.org/W3118795360","https://openalex.org/W4293846201","https://openalex.org/W4297672357","https://openalex.org/W4300511536","https://openalex.org/W4300677102","https://openalex.org/W6600213771","https://openalex.org/W6631190155","https://openalex.org/W6637162671","https://openalex.org/W6638667902","https://openalex.org/W6638836233","https://openalex.org/W6639703010","https://openalex.org/W6640212811","https://openalex.org/W6640425456","https://openalex.org/W6679955943","https://openalex.org/W6690026940","https://openalex.org/W6719080892","https://openalex.org/W6725939724","https://openalex.org/W6729756640","https://openalex.org/W6739868092","https://openalex.org/W6745591726","https://openalex.org/W6747769853","https://openalex.org/W6748711285","https://openalex.org/W6751351337","https://openalex.org/W6787972765"],"related_works":["https://openalex.org/W4385957115","https://openalex.org/W2061372042","https://openalex.org/W3047779762","https://openalex.org/W143502885","https://openalex.org/W1520030019","https://openalex.org/W42113618","https://openalex.org/W2103468410","https://openalex.org/W2071654592","https://openalex.org/W4361003569","https://openalex.org/W2981421796"],"abstract_inverted_index":{"Adding":[0],"small,":[1],"well":[2],"crafted":[3],"perturbations":[4],"to":[5,13,128,130],"the":[6,25,50,69,110,114,143],"pixel":[7],"values":[8],"of":[9,27,90,113,134,140,142],"input":[10],"images":[11,21],"leads":[12],"adversarial":[14],"examples,":[15],"so":[16],"called":[17,49],"because":[18],"these":[19],"perturbed":[20],"can":[22],"drastically":[23],"affect":[24],"accuracy":[26],"machine":[28],"learning":[29],"classifiers.":[30],"Defenses":[31],"against":[32],"such":[33],"attacks":[34],"are":[35,100],"being":[36],"studied,":[37],"often":[38],"with":[39,106,123],"varying":[40],"results.":[41],"In":[42,63],"this":[43],"study,":[44],"we":[45,137],"introduce":[46],"a":[47,65,91],"model":[48,122],"Stochastic-Gated":[51],"Partially":[52],"Binarized":[53],"Network":[54],"(SGBN":[55],"),":[56],"that":[57,71],"incorporates":[58],"binarization":[59],"and":[60,96,103,119,127,147],"input-dependent":[61],"stochasticity.":[62],"particular,":[64],"gate":[66,86],"module":[67,87],"learns":[68],"probability":[70],"individual":[72],"weights":[73],"in":[74,109],"corresponding":[75,107,149],"convolutional":[76,93,111],"filters":[77,108],"should":[78],"be":[79],"masked":[80],"(turned":[81],"on":[82],"or":[83],"off).":[84],"The":[85],"itself":[88],"consists":[89],"shallow":[92],"neural":[94],"network,":[95],"its":[97],"sigmoid":[98],"outputs":[99,146],"stochastically":[101],"binarized":[102],"pointwise":[104],"multiplied":[105],"layer":[112],"main":[115],"network.":[116],"We":[117],"test":[118],"compare":[120],"our":[121,135],"several":[124],"related":[125],"approaches,":[126],"try":[129],"gain":[131],"an":[132],"understanding":[133],"model,":[136],"visualize":[138],"activations":[139],"some":[141],"gating":[144],"network":[145],"their":[148],"filters.":[150]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}