{"id":"https://openalex.org/W4210697416","doi":"https://doi.org/10.1145/3510833","title":"Toward Adversary-aware Non-iterative Model Pruning through D ynamic N etwork R ewiring of DNNs","display_name":"Toward Adversary-aware Non-iterative Model Pruning through D ynamic N etwork R ewiring of DNNs","publication_year":2022,"publication_date":"2022-09-30","ids":{"openalex":"https://openalex.org/W4210697416","doi":"https://doi.org/10.1145/3510833"},"language":"en","primary_location":{"is_oa":true,"landing_page_url":"https://doi.org/10.1145/3510833","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3510833","source":{"id":"https://openalex.org/S136160450","display_name":"ACM Transactions in Embedded Computing Systems","issn_l":"1539-9087","issn":["1539-9087","1558-3465"],"is_oa":false,"is_in_doaj":false,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"version":"publishedVersion","is_accepted":true,"is_published":true},"type":"article","type_crossref":"journal-article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3510833","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5076002956","display_name":"Souvik Kundu","orcid":null},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Souvik Kundu","raw_affiliation_string":"University of Southern California, Los Angeles, California, USA","raw_affiliation_strings":["University of Southern California, Los Angeles, California, USA"]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091640552","display_name":"Yao Fu","orcid":"https://orcid.org/0000-0002-8931-3665"},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yao Fu","raw_affiliation_string":"University of Southern California, Los Angeles, California, USA","raw_affiliation_strings":["University of Southern California, Los Angeles, California, USA"]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001326971","display_name":"Bill Ye","orcid":null},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bill Ye","raw_affiliation_string":"University of Southern California, Los Angeles, California, USA","raw_affiliation_strings":["University of Southern California, Los Angeles, California, USA"]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084205024","display_name":"Peter A. Beerel","orcid":"https://orcid.org/0000-0002-8283-0168"},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Peter A. Beerel","raw_affiliation_string":"University of Southern California, Los Angeles, California, USA","raw_affiliation_strings":["University of Southern California, Los Angeles, California, USA"]},{"author_position":"last","author":{"id":"https://openalex.org/A5044650311","display_name":"Massoud Pedram","orcid":"https://orcid.org/0000-0002-2677-7307"},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Massoud Pedram","raw_affiliation_string":"University of Southern California, USA","raw_affiliation_strings":["University of Southern California, USA"]}],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"has_fulltext":true,"fulltext_origin":"pdf","cited_by_count":5,"cited_by_percentile_year":{"min":89,"max":91},"biblio":{"volume":"21","issue":"5","first_page":"1","last_page":"24"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Deep Learning Models","score":0.9997,"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 Deep Learning Models","score":0.9997,"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 in High-Dimensional Data","score":0.9951,"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/T12357","display_name":"Digital Image Forgery Detection and Identification","score":0.985,"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":[{"keyword":"model","score":0.2503},{"keyword":"adversary-aware","score":0.25},{"keyword":"non-iterative","score":0.25}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7898598},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.57861584},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.53133667},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5113887},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4931192},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.46756467},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.46234977},{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.44009936},{"id":"https://openalex.org/C162478608","wikidata":"https://www.wikidata.org/wiki/Q4011369","display_name":"Uncompressed video","level":4,"score":0.42067373},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.41095135},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.36609718},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.32894868},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.155381},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","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/C202474056","wikidata":"https://www.wikidata.org/wiki/Q1931635","display_name":"Video tracking","level":3,"score":0.0},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C6557445","wikidata":"https://www.wikidata.org/wiki/Q173113","display_name":"Agronomy","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}],"mesh":[],"locations_count":1,"locations":[{"is_oa":true,"landing_page_url":"https://doi.org/10.1145/3510833","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3510833","source":{"id":"https://openalex.org/S136160450","display_name":"ACM Transactions in Embedded Computing Systems","issn_l":"1539-9087","issn":["1539-9087","1558-3465"],"is_oa":false,"is_in_doaj":false,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"version":"publishedVersion","is_accepted":true,"is_published":true}],"best_oa_location":{"is_oa":true,"landing_page_url":"https://doi.org/10.1145/3510833","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3510833","source":{"id":"https://openalex.org/S136160450","display_name":"ACM Transactions in Embedded Computing Systems","issn_l":"1539-9087","issn":["1539-9087","1558-3465"],"is_oa":false,"is_in_doaj":false,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"version":"publishedVersion","is_accepted":true,"is_published":true},"sustainable_development_goals":[{"score":0.55,"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure"}],"grants":[],"referenced_works_count":26,"referenced_works":["https://openalex.org/W2102605133","https://openalex.org/W2119112357","https://openalex.org/W2160815625","https://openalex.org/W2194775991","https://openalex.org/W2570343428","https://openalex.org/W2592929672","https://openalex.org/W2618043096","https://openalex.org/W2886851211","https://openalex.org/W2962710014","https://openalex.org/W2962818002","https://openalex.org/W2963145730","https://openalex.org/W2963363373","https://openalex.org/W2963485691","https://openalex.org/W2963952467","https://openalex.org/W2973907236","https://openalex.org/W2993801694","https://openalex.org/W3006098440","https://openalex.org/W3009751875","https://openalex.org/W3091610286","https://openalex.org/W3128829362","https://openalex.org/W3161703143","https://openalex.org/W3175451538","https://openalex.org/W3177096435","https://openalex.org/W3193285461","https://openalex.org/W3202425151","https://openalex.org/W4292363360"],"related_works":["https://openalex.org/W2294590153","https://openalex.org/W2950183588","https://openalex.org/W3080754722","https://openalex.org/W4383221314","https://openalex.org/W3093978547","https://openalex.org/W2953536436","https://openalex.org/W3203790781","https://openalex.org/W2997056298","https://openalex.org/W2738001131","https://openalex.org/W4285785480"],"ngrams_url":"https://api.openalex.org/works/W4210697416/ngrams","abstract_inverted_index":{"We":[0,287],"present":[1,176],"a":[2,41,47,143,178],"dynamic":[3],"network":[4,13],"rewiring":[5],"(DNR)":[6],"method":[7,37,95,166],"to":[8,110,114,120,151,195,235,291,311],"generate":[9],"pruned":[10,85],"deep":[11],"neural":[12],"(DNN)":[14],"models":[15,190,271,307],"that":[16,52,107,125,184,196,265],"both":[17,153],"are":[18],"robust":[19,57,116,122,187],"against":[20],"adversarially":[21],"generated":[22],"images":[23],"and":[24,133,147,155,221,225,275,298,302,308],"maintain":[25],"high":[26],"accuracy":[27],"on":[28,40,68,223,232,246],"clean":[29,256,274],"images.":[30],"In":[31,118],"particular,":[32],"the":[33,74,81,84,93,99,111,130,161,164,168,204,236,248],"disclosed":[34,208],"DNR":[35,94,132],"training":[36,61,128,145,172,182,192,209],"is":[38,108,282],"based":[39,67],"unified":[42],"constrained":[43],"optimization":[44],"formulation":[45],"using":[46],"novel":[48],"hybrid":[49,75],"loss":[50,76],"function":[51],"merges":[53],"sparse":[54,102],"learning":[55],"with":[56,141,214,230,272],"adversarial":[58,171,258,276],"training.":[59,201],"This":[60],"strategy":[62],"dynamically":[63],"adjusts":[64],"inter-layer":[65],"connectivity":[66],"per-layer":[69],"normalized":[70],"momentum":[71],"computed":[72],"from":[73],"function.":[77],"To":[78,159,202],"further":[79],"improve":[80],"robustness":[82],"of":[83,92,101,163,197,206,254,314],"models,":[86,218,239],"we":[87,97,174],"propose":[88],"DNR++,":[89],"an":[90,136,198],"extension":[91],"where":[96],"introduce":[98],"idea":[100],"parametric":[103],"Gaussian":[104],"noise":[105],"tensor":[106],"added":[109],"weight":[112],"tensors":[113],"yield":[115,186],"regularization.":[117],"contrast":[119],"existing":[121],"pruning":[123,139],"frameworks":[124],"require":[126],"multiple":[127],"iterations,":[129],"proposed":[131,165],"DNR++":[134],"achieve":[135],"overall":[137],"target":[138],"ratio":[140],"only":[142],"single":[144],"iteration":[146],"can":[148,185],"be":[149],"tuned":[150],"support":[152],"irregular":[154],"structured":[156],"channel":[157],"pruning.":[158],"demonstrate":[160],"efficacy":[162],"under":[167],"no-increased-training-time":[169],"\u201cfree\u201d":[170],"scenario,":[173],"finally":[175],"FDNR++,":[177],"simple":[179],"yet":[180,188],"effective":[181],"modification":[183],"compressed":[189,270],"requiring":[191],"time":[193],"comparable":[194],"unpruned":[199],"non-adversarial":[200],"evaluate":[203],"merits":[205],"our":[207,240,266,305,315],"methods,":[210],"experiments":[211,263],"were":[212],"performed":[213],"two":[215],"widely":[216],"accepted":[217],"namely":[219],"VGG16":[220,231],"ResNet18,":[222],"CIFAR-10":[224],"CIFAR-100":[226],"as":[227,229],"well":[228],"Tiny-ImageNet.":[233],"Compared":[234],"baseline":[237],"uncompressed":[238],"methods":[241,267],"provide":[242,288],"over":[243],"20\u00d7":[244],"compression":[245],"all":[247],"datasets":[249],"without":[250],"any":[251],"significant":[252],"drop":[253],"either":[255],"or":[257],"classification":[259,278],"performance.":[260],"Moreover,":[261],"extensive":[262],"show":[264],"consistently":[268],"find":[269],"better":[273],"image":[277],"performance":[279],"than":[280],"what":[281],"achievable":[283],"through":[284],"state-of-the-art":[285],"alternatives.":[286],"insightful":[289],"observations":[290],"help":[292],"make":[293],"various":[294],"model,":[295],"parameter":[296],"density,":[297],"prune-type":[299],"selection":[300],"choices":[301],"have":[303],"open-sourced":[304],"saved":[306],"test":[309],"codes":[310],"ensure":[312],"reproducibility":[313],"results.":[316]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W4210697416","counts_by_year":[{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":1}],"updated_date":"2024-03-06T12:54:02.585706","created_date":"2022-02-08"}