{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,17]],"date-time":"2026-06-17T05:11:39Z","timestamp":1781673099724,"version":"3.54.5"},"reference-count":52,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"1","license":[{"start":{"date-parts":[[2025,2,1]],"date-time":"2025-02-01T00:00:00Z","timestamp":1738368000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2025,2,1]],"date-time":"2025-02-01T00:00:00Z","timestamp":1738368000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,2,1]],"date-time":"2025-02-01T00:00:00Z","timestamp":1738368000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"Coordena\u00e7\u00e3o de Aperfei\u00e7oamento de Pessoal de N\u00edvel Superior - Brasil (CAPES) - Finance Code 001, CNPq, PR2\/UFRJ, FAPERJ","award":["E-26\/203.211\/2017"],"award-info":[{"award-number":["E-26\/203.211\/2017"]}]},{"name":"Coordena\u00e7\u00e3o de Aperfei\u00e7oamento de Pessoal de N\u00edvel Superior - Brasil (CAPES) - Finance Code 001, CNPq, PR2\/UFRJ, FAPERJ","award":["E-26\/010.002174\/2019"],"award-info":[{"award-number":["E-26\/010.002174\/2019"]}]},{"name":"Coordena\u00e7\u00e3o de Aperfei\u00e7oamento de Pessoal de N\u00edvel Superior - Brasil (CAPES) - Finance Code 001, CNPq, PR2\/UFRJ, FAPERJ","award":["E-26\/201.300\/2021"],"award-info":[{"award-number":["E-26\/201.300\/2021"]}]},{"DOI":"10.13039\/501100001807","name":"Funda\u00e7\u00e3o de Amparo \u00e0 Pesquisa do Estado de S\u00e3o Paulo","doi-asserted-by":"publisher","award":["15\/24494-8"],"award-info":[{"award-number":["15\/24494-8"]}],"id":[{"id":"10.13039\/501100001807","id-type":"DOI","asserted-by":"publisher"}]},{"name":"SERB, Govt. of India, through the Core Research","award":["CRG\/2022\/008807"],"award-info":[{"award-number":["CRG\/2022\/008807"]}]},{"name":"MATRICS","award":["MTR\/2021\/000645"],"award-info":[{"award-number":["MTR\/2021\/000645"]}]},{"name":"DST-Inria Targeted Programme"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Netw. Serv. Manage."],"published-print":{"date-parts":[[2025,2]]},"DOI":"10.1109\/tnsm.2024.3479076","type":"journal-article","created":{"date-parts":[[2024,10,11]],"date-time":"2024-10-11T17:21:29Z","timestamp":1728667289000},"page":"107-120","source":"Crossref","is-referenced-by-count":6,"title":["UCBEE: A Multi Armed Bandit Approach for Early-Exit in Neural Networks"],"prefix":"10.1109","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6763-7255","authenticated-orcid":false,"given":"Roberto G.","family":"Pacheco","sequence":"first","affiliation":[{"name":"Computer Science Department, Universidade Federal Fluminense, Rio das Ostras, Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-8696-6950","authenticated-orcid":false,"given":"Divya J.","family":"Bajpai","sequence":"additional","affiliation":[{"name":"Department of Industrial Engineering and Operations Research, Indian Institute of Technology Bombay, Mumbai, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0946-5018","authenticated-orcid":false,"given":"Mark","family":"Shifrin","sequence":"additional","affiliation":[{"name":"School of Electrical and Computer Engineering, Ben-Gurion University, Beer-Sheva, Israel"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6921-7756","authenticated-orcid":false,"given":"Rodrigo S.","family":"Couto","sequence":"additional","affiliation":[{"name":"Electronic and Computer Engineering Department, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8953-4003","authenticated-orcid":false,"given":"Daniel Sadoc","family":"Menasch\u00e9","sequence":"additional","affiliation":[{"name":"Institute of Computing, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1807-5487","authenticated-orcid":false,"given":"Manjesh K.","family":"Hanawal","sequence":"additional","affiliation":[{"name":"Department of Industrial Engineering and Operations Research, Indian Institute of Technology Bombay, Mumbai, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8752-9382","authenticated-orcid":false,"given":"Miguel Elias M.","family":"Campista","sequence":"additional","affiliation":[{"name":"Electronic and Computer Engineering Department, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","first-page":"1","article-title":"ImageNet classification with deep convolutional neural networks","volume-title":"Proc. Neural Inf. Process. Syst.","volume":"25","author":"Krizhevsky"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jnca.2021.103213"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/N18-1202"},{"key":"ref4","article-title":"BERT: Pre-training of deep bidirectional transformers for language understanding","author":"Devlin","year":"2018","journal-title":"arXiv:1810.04805"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.48550\/ARXIV.1907.11692"},{"key":"ref6","article-title":"Release strategies and the social impacts of language models","author":"Solaiman","year":"2019","journal-title":"arXiv:1908.09203"},{"key":"ref7","first-page":"5754","article-title":"XLNet: Generalized autoregressive pretraining for language understanding","volume-title":"Proc. Neural Inf. Process. Syst. (NeurIPS)","volume":"32","author":"Yang"},{"key":"ref8","volume-title":"Language models are unsupervised multitask learners.","year":"2020"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/ICPR.2016.7900006"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/ISCC50000.2020.9219647"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1145\/3372224.3419194"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/GLOBECOM46510.2021.9685469"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/ICC42927.2021.9500760"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/ICCVW54120.2021.00213"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/ISSRE5003.2020.00011"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/QoMEX.2016.7498955"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.acl-main.204"},{"key":"ref18","article-title":"Towards efficient NLP: A standard evaluation and a strong baseline","author":"Liu","year":"2021","journal-title":"arXiv:2110.07038"},{"key":"ref19","first-page":"3168","article-title":"Online algorithm for unsupervised sensor selection","volume-title":"Proc. Int. Conf. Artif. Intell. Stat.","author":"Verma"},{"key":"ref20","article-title":"Caltech-256 object category dataset","author":"Griffin","year":"2007"},{"key":"ref21","article-title":"Controlling computation versus quality for neural sequence models","author":"Bapna","year":"2020","journal-title":"arXiv:2002.07106"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2024.findings-acl.101"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1145\/1718487.1718538"},{"key":"ref24","article-title":"A panda? No, it\u2019s a sloth: Slowdown attacks on adaptive multi-exit neural network inference","author":"Hong","year":"2020","journal-title":"arXiv:2010.02432"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1145\/3657283"},{"key":"ref26","first-page":"18330","article-title":"Bert loses patience: Fast and robust inference with early exit","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"33","author":"Zhou"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP43922.2022.9746330"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1145\/3345768.3355917"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/SEC50012.2020.00014"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/TWC.2019.2946140"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/SiPS47522.2019.9020551"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/ISOCC50952.2020.9333079"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1007\/s12559-020-09734-4"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/ICDCS.2017.226"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1016\/j.jnca.2023.103679"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/ICC51166.2024.10622954"},{"key":"ref37","first-page":"1","article-title":"Depth-adaptive transformer","volume-title":"Proc. Int. Conf. Learn. Represent. (ICLR)","author":"Elbayad"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1145\/3459637.3482335"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/CCGrid51090.2021.00011"},{"key":"ref40","first-page":"1","article-title":"Unsupervised early exit in DNNs with multiple exits","volume-title":"Proc. ACM Int. Conf. AI-ML Syst.","author":"Narayan"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/ICC45041.2023.10279243"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/TC.2023.3333189"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2024.3439852"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1145\/3626788"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1023\/A:1013689704352"},{"key":"ref46","article-title":"MobileNets: Efficient convolutional neural networks for mobile vision applications","author":"Howard","year":"2017","journal-title":"arXiv:1704.04861"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00474"},{"key":"ref48","article-title":"Very deep convolutional networks for large-scale image recognition","author":"Simonyan","year":"2014","journal-title":"arXiv:1409.1556"},{"key":"ref49","volume-title":"Deep Learning","volume":"1","author":"Goodfellow","year":"2016"},{"key":"ref50","first-page":"249","article-title":"Understanding the difficulty of training deep feedforward neural networks","volume-title":"Proc. Int. Conf. Artif. Intell. Stat.","author":"Glorot"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1109\/INFOCOM.2019.8737653"}],"container-title":["IEEE Transactions on Network and Service Management"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/4275028\/10927606\/10714362.pdf?arnumber=10714362","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,3,17]],"date-time":"2025-03-17T17:40:59Z","timestamp":1742233259000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10714362\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,2]]},"references-count":52,"journal-issue":{"issue":"1"},"URL":"https:\/\/doi.org\/10.1109\/tnsm.2024.3479076","relation":{},"ISSN":["1932-4537","2373-7379"],"issn-type":[{"value":"1932-4537","type":"electronic"},{"value":"2373-7379","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,2]]}}}