{"id":"https://openalex.org/W4387869899","doi":"https://doi.org/10.1109/icc45041.2023.10279243","title":"AdaEE: Adaptive Early-Exit DNN Inference Through Multi-Armed Bandits","display_name":"AdaEE: Adaptive Early-Exit DNN Inference Through Multi-Armed Bandits","publication_year":2023,"publication_date":"2023-05-28","ids":{"openalex":"https://openalex.org/W4387869899","doi":"https://doi.org/10.1109/icc45041.2023.10279243"},"language":"en","primary_location":{"id":"doi:10.1109/icc45041.2023.10279243","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icc45041.2023.10279243","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICC 2023 - IEEE International Conference on Communications","raw_type":"proceedings-article"},"type":"conference-paper","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/A5081714773","display_name":"Roberto G. Pacheco","orcid":"https://orcid.org/0000-0002-6763-7255"},"institutions":[{"id":"https://openalex.org/I122140584","display_name":"Universidade Federal do Rio de Janeiro","ror":"https://ror.org/03490as77","country_code":"BR","type":"education","lineage":["https://openalex.org/I122140584"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Roberto G. Pacheco","raw_affiliation_strings":["Universidade Federal do Rio de Janeiro (Brazil)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universidade Federal do Rio de Janeiro (Brazil)","institution_ids":["https://openalex.org/I122140584"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061539306","display_name":"Mark Shifrin","orcid":"https://orcid.org/0000-0003-0946-5018"},"institutions":[{"id":"https://openalex.org/I124227911","display_name":"Ben-Gurion University of the Negev","ror":"https://ror.org/05tkyf982","country_code":"IL","type":"education","lineage":["https://openalex.org/I124227911"]}],"countries":["IL"],"is_corresponding":false,"raw_author_name":"Mark Shifrin","raw_affiliation_strings":["Ben-Gurion University (Israel)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ben-Gurion University (Israel)","institution_ids":["https://openalex.org/I124227911"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044922664","display_name":"Rodrigo S. Couto","orcid":"https://orcid.org/0000-0002-6921-7756"},"institutions":[{"id":"https://openalex.org/I122140584","display_name":"Universidade Federal do Rio de Janeiro","ror":"https://ror.org/03490as77","country_code":"BR","type":"education","lineage":["https://openalex.org/I122140584"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Rodrigo S. Couto","raw_affiliation_strings":["Universidade Federal do Rio de Janeiro (Brazil)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universidade Federal do Rio de Janeiro (Brazil)","institution_ids":["https://openalex.org/I122140584"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034604991","display_name":"Daniel Sadoc Menasch\u00e9","orcid":"https://orcid.org/0000-0002-8953-4003"},"institutions":[{"id":"https://openalex.org/I122140584","display_name":"Universidade Federal do Rio de Janeiro","ror":"https://ror.org/03490as77","country_code":"BR","type":"education","lineage":["https://openalex.org/I122140584"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Daniel S. Menasch\u00e9","raw_affiliation_strings":["Universidade Federal do Rio de Janeiro (Brazil)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universidade Federal do Rio de Janeiro (Brazil)","institution_ids":["https://openalex.org/I122140584"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057858044","display_name":"Manjesh K. Hanawal","orcid":"https://orcid.org/0000-0002-1807-5487"},"institutions":[{"id":"https://openalex.org/I162827531","display_name":"Indian Institute of Technology Bombay","ror":"https://ror.org/02qyf5152","country_code":"IN","type":"education","lineage":["https://openalex.org/I162827531"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Manjesh K. Hanawal","raw_affiliation_strings":["Indian Institute of Technology Bombay (India)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Indian Institute of Technology Bombay (India)","institution_ids":["https://openalex.org/I162827531"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5083970479","display_name":"Miguel Elias M. Campista","orcid":"https://orcid.org/0000-0002-8752-9382"},"institutions":[{"id":"https://openalex.org/I122140584","display_name":"Universidade Federal do Rio de Janeiro","ror":"https://ror.org/03490as77","country_code":"BR","type":"education","lineage":["https://openalex.org/I122140584"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Miguel Elias M. Campista","raw_affiliation_strings":["Universidade Federal do Rio de Janeiro (Brazil)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universidade Federal do Rio de Janeiro (Brazil)","institution_ids":["https://openalex.org/I122140584"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.0503,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.85068674,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"3726","last_page":"3731"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9991000294685364,"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"}},"topics":[{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9991000294685364,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9987000226974487,"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/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9965000152587891,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7532125115394592},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6828168630599976},{"id":"https://openalex.org/keywords/regret","display_name":"Regret","score":0.6440523862838745},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.6301847696304321},{"id":"https://openalex.org/keywords/edge-device","display_name":"Edge device","score":0.617356538772583},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.6043035984039307},{"id":"https://openalex.org/keywords/distortion","display_name":"Distortion (music)","score":0.5174422860145569},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.48152169585227966},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.47466328740119934},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.4604511857032776},{"id":"https://openalex.org/keywords/cloud-computing","display_name":"Cloud computing","score":0.4418703317642212},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3795425295829773},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3591209053993225},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.12221822142601013}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7532125115394592},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6828168630599976},{"id":"https://openalex.org/C50817715","wikidata":"https://www.wikidata.org/wiki/Q79895177","display_name":"Regret","level":2,"score":0.6440523862838745},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6301847696304321},{"id":"https://openalex.org/C138236772","wikidata":"https://www.wikidata.org/wiki/Q25098575","display_name":"Edge device","level":3,"score":0.617356538772583},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.6043035984039307},{"id":"https://openalex.org/C126780896","wikidata":"https://www.wikidata.org/wiki/Q899871","display_name":"Distortion (music)","level":4,"score":0.5174422860145569},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.48152169585227966},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47466328740119934},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.4604511857032776},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.4418703317642212},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3795425295829773},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3591209053993225},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.12221822142601013},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C194257627","wikidata":"https://www.wikidata.org/wiki/Q211554","display_name":"Amplifier","level":3,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icc45041.2023.10279243","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icc45041.2023.10279243","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICC 2023 - IEEE International Conference on Communications","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy","score":0.9100000262260437}],"awards":[{"id":"https://openalex.org/G6579851573","display_name":null,"funder_award_id":"E-26/203.211/2017,E-26/010.002174/2019,E-26/201.300/2021","funder_id":"https://openalex.org/F4320321091","funder_display_name":"Coordena\u00e7\u00e3o de Aperfei\u00e7oamento de Pessoal de N\u00edvel Superior"},{"id":"https://openalex.org/G7349480107","display_name":"Communications and processing of big data in cloud and fog computing","funder_award_id":"15/24494-8","funder_id":"https://openalex.org/F4320320997","funder_display_name":"Funda\u00e7\u00e3o de Amparo \u00e0 Pesquisa do Estado de S\u00e3o Paulo"}],"funders":[{"id":"https://openalex.org/F4320320997","display_name":"Funda\u00e7\u00e3o de Amparo \u00e0 Pesquisa do Estado de S\u00e3o Paulo","ror":"https://ror.org/02ddkpn78"},{"id":"https://openalex.org/F4320321091","display_name":"Coordena\u00e7\u00e3o de Aperfei\u00e7oamento de Pessoal de N\u00edvel Superior","ror":"https://ror.org/00x0ma614"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W1576445103","https://openalex.org/W2163605009","https://openalex.org/W2168405694","https://openalex.org/W2568772110","https://openalex.org/W2613962421","https://openalex.org/W2920031528","https://openalex.org/W2962677625","https://openalex.org/W2963980515","https://openalex.org/W2964348567","https://openalex.org/W2980856918","https://openalex.org/W2990958518","https://openalex.org/W3012024854","https://openalex.org/W3021083954","https://openalex.org/W3049640275","https://openalex.org/W3093589362","https://openalex.org/W3094307698","https://openalex.org/W3100646146","https://openalex.org/W3102278250","https://openalex.org/W3102767875","https://openalex.org/W3126228810","https://openalex.org/W3130607817","https://openalex.org/W3191795420","https://openalex.org/W3200649648","https://openalex.org/W3208262036","https://openalex.org/W4225966323","https://openalex.org/W4236099117","https://openalex.org/W4296605770","https://openalex.org/W4297775537","https://openalex.org/W4376852236","https://openalex.org/W6684191040","https://openalex.org/W6737664043"],"related_works":["https://openalex.org/W2971351794","https://openalex.org/W4376155396","https://openalex.org/W1947085858","https://openalex.org/W3013760193","https://openalex.org/W3162668736","https://openalex.org/W4366999913","https://openalex.org/W4281678247","https://openalex.org/W4381489698","https://openalex.org/W3014007418","https://openalex.org/W3131458535"],"abstract_inverted_index":{"Deep":[0,134],"Neural":[1,135],"Networks":[2,136],"(DNNs)":[3],"are":[4],"widely":[5],"used":[6],"to":[7,28,88,101,141,206],"solve":[8],"a":[9,55,61,138,176,193],"growing":[10],"number":[11],"of":[12,117],"tasks,":[13],"such":[14],"as":[15],"image":[16,98],"classification.":[17],"However,":[18],"their":[19,45],"deployment":[20],"at":[21,54,70],"resource-constrained":[22],"devices":[23],"still":[24],"poses":[25],"challenges":[26,39],"related":[27],"energy":[29],"consumption":[30],"and":[31,121,186,189],"delay":[32],"over-heads.":[33],"Early-Exit":[34,132],"DNNs":[35],"(EE-DNNs)":[36],"address":[37],"the":[38,52,65,71,81,85,89,112,118,144,151,202],"by":[40],"adding":[41],"side":[42,56],"branches":[43],"through":[44],"architecture.":[46],"Under":[47],"an":[48],"edge-cloud":[49],"co-inference,":[50],"if":[51],"confidence":[53,63,145],"branch":[57],"is":[58,67],"larger":[59],"than":[60],"fixed":[62],"threshold,":[64],"inference":[66,86],"performed":[68],"completely":[69],"edge":[72,82],"device,":[73],"saving":[74],"computation":[75],"for":[76,97,156,180],"more":[77],"difficult":[78],"observations.":[79],"Otherwise,":[80],"device":[83],"offloads":[84],"task":[87],"cloud,":[90],"incurring":[91],"overhead.":[92],"Despite":[93],"its":[94],"success,":[95],"EE-DNNs":[96],"classification":[99],"have":[100],"cope":[102,125],"with":[103,126,182],"distorted":[104],"images.":[105],"The":[106],"baseline":[107],"distortion":[108,184],"level":[109],"depends":[110],"on":[111,148],"environmental":[113],"context,":[114,149],"e.g.,":[115],"time":[116],"day,":[119],"lighting,":[120],"weather":[122],"conditions.":[123,166],"To":[124],"varying":[127,207],"distortion,":[128],"we":[129],"propose":[130],"Adaptive":[131],"in":[133],"(AdaEE),":[137],"novel":[139],"algorithm":[140],"dynamically":[142],"adjust":[143],"threshold":[146],"based":[147],"leveraging":[150],"Upper":[152],"Confidence":[153],"Bound":[154],"(UCB)":[155],"that":[157,170],"matter.":[158],"AdaEE":[159,191],"provably":[160],"achieves":[161],"logarithmic":[162],"regret":[163,196],"under":[164],"mild":[165],"We":[167],"experimentally":[168],"verify":[169],"1)":[171],"convergence":[172],"occurs":[173],"after":[174],"collecting":[175],"few":[177],"thousand":[178],"observations":[179],"images":[181],"different":[183],"levels":[185],"overhead":[187],"values,":[188],"2)":[190],"obtains":[192],"lower":[194],"cumulative":[195],"when":[197],"compared":[198],"against":[199],"alternatives":[200],"using":[201],"Caltech-256":[203],"dataset":[204],"subject":[205],"distortion.":[208]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":3}],"updated_date":"2026-08-11T07:18:39.950985","created_date":"2025-10-10T00:00:00"}