{"id":"https://openalex.org/W4289655474","doi":"https://doi.org/10.1109/isit50566.2022.9834778","title":"Binary Classification Under \u2113 <sub>0</sub> Attacks for General Noise Distribution","display_name":"Binary Classification Under \u2113 <sub>0</sub> Attacks for General Noise Distribution","publication_year":2022,"publication_date":"2022-06-26","ids":{"openalex":"https://openalex.org/W4289655474","doi":"https://doi.org/10.1109/isit50566.2022.9834778"},"language":"en","primary_location":{"id":"doi:10.1109/isit50566.2022.9834778","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isit50566.2022.9834778","pdf_url":null,"source":{"id":"https://openalex.org/S4363604560","display_name":"2022 IEEE International Symposium on Information Theory (ISIT)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Symposium on Information Theory (ISIT)","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/A5077115606","display_name":"Payam Delgosha","orcid":"https://orcid.org/0000-0003-0266-9237"},"institutions":[{"id":"https://openalex.org/I157725225","display_name":"University of Illinois Urbana-Champaign","ror":"https://ror.org/047426m28","country_code":"US","type":"education","lineage":["https://openalex.org/I157725225"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Payam Delgosha","raw_affiliation_strings":["Uni. of Illinois at Urbana-Champaign"],"affiliations":[{"raw_affiliation_string":"Uni. of Illinois at Urbana-Champaign","institution_ids":["https://openalex.org/I157725225"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059354479","display_name":"Hamed Hassani","orcid":"https://orcid.org/0000-0002-9448-8750"},"institutions":[{"id":"https://openalex.org/I36788626","display_name":"California University of Pennsylvania","ror":"https://ror.org/01spssf70","country_code":"US","type":"education","lineage":["https://openalex.org/I36788626"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hamed Hassani","raw_affiliation_strings":["Uni. of Pennsylvania"],"affiliations":[{"raw_affiliation_string":"Uni. of Pennsylvania","institution_ids":["https://openalex.org/I36788626"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5040270189","display_name":"Ramtin Pedarsani","orcid":"https://orcid.org/0000-0002-1126-0292"},"institutions":[{"id":"https://openalex.org/I154570441","display_name":"University of California, Santa Barbara","ror":"https://ror.org/02t274463","country_code":"US","type":"education","lineage":["https://openalex.org/I154570441"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ramtin Pedarsani","raw_affiliation_strings":["Uni. of California Santa Barbara"],"affiliations":[{"raw_affiliation_string":"Uni. of California Santa Barbara","institution_ids":["https://openalex.org/I154570441"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5077115606"],"corresponding_institution_ids":["https://openalex.org/I157725225"],"apc_list":null,"apc_paid":null,"fwci":0.1046,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.27916468,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1731","last_page":"1736"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9993000030517578,"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":0.9993000030517578,"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/T12131","display_name":"Wireless Signal Modulation Classification","score":0.9921000003814697,"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/T10964","display_name":"Wireless Communication Security Techniques","score":0.9824000000953674,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6848482489585876},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.6426127552986145},{"id":"https://openalex.org/keywords/binary-number","display_name":"Binary number","score":0.4659693241119385},{"id":"https://openalex.org/keywords/binary-classification","display_name":"Binary classification","score":0.4335956871509552},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4205589294433594},{"id":"https://openalex.org/keywords/distribution","display_name":"Distribution (mathematics)","score":0.4203149378299713},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.35712602734565735},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.34149008989334106},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.32324907183647156},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.20771947503089905},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.15997374057769775}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6848482489585876},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.6426127552986145},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.4659693241119385},{"id":"https://openalex.org/C66905080","wikidata":"https://www.wikidata.org/wiki/Q17005494","display_name":"Binary classification","level":3,"score":0.4335956871509552},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4205589294433594},{"id":"https://openalex.org/C110121322","wikidata":"https://www.wikidata.org/wiki/Q865811","display_name":"Distribution (mathematics)","level":2,"score":0.4203149378299713},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.35712602734565735},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.34149008989334106},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.32324907183647156},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.20771947503089905},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15997374057769775},{"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/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isit50566.2022.9834778","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isit50566.2022.9834778","pdf_url":null,"source":{"id":"https://openalex.org/S4363604560","display_name":"2022 IEEE International Symposium on Information Theory (ISIT)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Symposium on Information Theory (ISIT)","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":43,"referenced_works":["https://openalex.org/W9657784","https://openalex.org/W1525038591","https://openalex.org/W1664169458","https://openalex.org/W1673923490","https://openalex.org/W1945616565","https://openalex.org/W2046135376","https://openalex.org/W2180612164","https://openalex.org/W2432142698","https://openalex.org/W2918967742","https://openalex.org/W2931892667","https://openalex.org/W2963076808","https://openalex.org/W2963143631","https://openalex.org/W2963274426","https://openalex.org/W2963857521","https://openalex.org/W2964082701","https://openalex.org/W2964152294","https://openalex.org/W2965595599","https://openalex.org/W2980393746","https://openalex.org/W2998293245","https://openalex.org/W3132352336","https://openalex.org/W3141848572","https://openalex.org/W3212995846","https://openalex.org/W4205125306","https://openalex.org/W4287550623","https://openalex.org/W4287753328","https://openalex.org/W4289655474","https://openalex.org/W4293846201","https://openalex.org/W6600428322","https://openalex.org/W6637162671","https://openalex.org/W6637304703","https://openalex.org/W6640425456","https://openalex.org/W6717848421","https://openalex.org/W6739868092","https://openalex.org/W6748475379","https://openalex.org/W6754733991","https://openalex.org/W6760418104","https://openalex.org/W6760684019","https://openalex.org/W6766613003","https://openalex.org/W6780248507","https://openalex.org/W6787757517","https://openalex.org/W6791011698","https://openalex.org/W6792488678","https://openalex.org/W6796782478"],"related_works":["https://openalex.org/W1993278628","https://openalex.org/W2090073005","https://openalex.org/W2134880816","https://openalex.org/W2060911701","https://openalex.org/W2183768935","https://openalex.org/W2093709274","https://openalex.org/W2004123705","https://openalex.org/W2363205410","https://openalex.org/W2372484735","https://openalex.org/W2029119259"],"abstract_inverted_index":{"Adversarial":[0],"examples":[1],"have":[2],"recently":[3],"drawn":[4],"considerable":[5],"attention":[6],"in":[7,20,25,45,53,85,116,160,189,208],"the":[8,15,21,43,65,70,86,102,113,136,167,185,190,193,209,220],"field":[9],"of":[10,83,105,135,192],"machine":[11,118],"learning":[12,119],"due":[13],"to":[14,42,101,110,120,141,171],"fact":[16],"that":[17,38,211,218],"small":[18],"perturbations":[19,41],"data":[22,44,133,179],"can":[23,39,78,96,182,197,222,232],"result":[24],"major":[26],"performance":[27],"degradation.":[28],"This":[29],"phenomenon":[30],"is":[31,67,169],"usually":[32],"modeled":[33],"by":[34,69],"a":[35,46,54,80,126,148,153,205,213,236],"malicious":[36],"adversary":[37,66,168,221],"apply":[40],"constrained":[47,68],"fashion,":[48],"such":[49],"as":[50,164,166],"being":[51],"bounded":[52],"certain":[55,81],"norm.":[56],"In":[57],"this":[58,62,106,122],"paper,":[59],"we":[60,108,181,196,203,216],"study":[61],"problem":[63],"when":[64],"\u2113":[71],"<inf":[72],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[73],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">0</inf>":[74],"norm;":[75],"i.e.,":[76],"it":[77,95],"perturb":[79,97,172,223],"number":[82],"coordinates":[84],"input,":[87],"but":[88],"has":[89],"no":[90,173,230],"limit":[91],"on":[92],"how":[93],"much":[94],"those":[98],"coordinates.":[99],"Due":[100],"combinatorial":[103],"nature":[104],"setting,":[107],"need":[109],"go":[111],"beyond":[112],"standard":[114],"techniques":[115],"robust":[117],"address":[121],"problem.":[123],"We":[124,146],"consider":[125],"binary":[127],"classification":[128,149,187],"scenario":[129],"where":[130],"d":[131,177,227],"noisy":[132],"samples":[134],"true":[137],"label":[138],"are":[139],"provided":[140],"us":[142],"after":[143],"adversarial":[144],"perturbations.":[145],"introduce":[147],"method":[150],"which":[151],"employs":[152],"nonlinear":[154],"component":[155],"called":[156],"truncation,":[157],"and":[158],"show":[159,217],"an":[161],"asymptotic":[162],"scenario,":[163],"long":[165],"restricted":[170],"more":[174,224],"than":[175,225,235],"$\\sqrt":[176,226],"$":[178,228],"samples,":[180],"almost":[183],"achieve":[184],"optimal":[186],"error":[188],"absence":[191],"adversary,":[194],"i.e.":[195],"completely":[198],"neutralize":[199],"adversary\u2019s":[200],"effect.":[201],"Surprisingly,":[202],"observe":[204],"phase":[206],"transition":[207],"sense":[210],"using":[212],"converse":[214],"argument,":[215],"if":[219],"coordinates,":[229],"classifier":[231],"do":[233],"better":[234],"random":[237],"guess.":[238]},"counts_by_year":[{"year":2022,"cited_by_count":1}],"updated_date":"2026-03-25T13:04:00.132906","created_date":"2025-10-10T00:00:00"}
