{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T13:30:44Z","timestamp":1740144644712,"version":"3.37.3"},"reference-count":18,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"2","license":[{"start":{"date-parts":[[2021,7,1]],"date-time":"2021-07-01T00:00:00Z","timestamp":1625097600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2021,7,1]],"date-time":"2021-07-01T00:00:00Z","timestamp":1625097600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2021,7,1]],"date-time":"2021-07-01T00:00:00Z","timestamp":1625097600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Comput. Arch. Lett."],"published-print":{"date-parts":[[2021,7,1]]},"DOI":"10.1109\/lca.2021.3101505","type":"journal-article","created":{"date-parts":[[2021,8,4]],"date-time":"2021-08-04T20:26:04Z","timestamp":1628108764000},"page":"98-101","source":"Crossref","is-referenced-by-count":0,"title":["Guessing Outputs of Dynamically Pruned CNNs Using Memory Access Patterns"],"prefix":"10.1109","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9728-5708","authenticated-orcid":false,"given":"Benjamin","family":"Wu","sequence":"first","affiliation":[]},{"given":"Trishita","family":"Tiwari","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6409-9888","authenticated-orcid":false,"given":"G. Edward","family":"Suh","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9127-0089","authenticated-orcid":false,"given":"Aaron B.","family":"Wagner","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"article-title":"PyTorch: An imperative style, high-performance deep learning library","year":"2019","author":"paszke","key":"ref10"},{"key":"ref11","first-page":"265","article-title":"TensorFlow: A system for large-scale machine learning","author":"abadi","year":"2016","journal-title":"Proc 12th USENIX Symp Oper Syst Des Implementation"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.205"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01234-2_48"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46493-0_40"},{"article-title":"Bayesian compression for deep learning","year":"2017","author":"louizos","key":"ref15"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/JPROC.2017.2761740"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2020.107461"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939785"},{"article-title":"Dynamic network surgery for efficient DNNs","year":"2016","author":"guo","key":"ref4"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i04.6098"},{"key":"ref6","first-page":"1","article-title":"Reverse engineering convolutional neural networks through side-channel information leaks","author":"hua","year":"2018","journal-title":"Proc 55th ACM\/ESDA\/IEEE Des Automat Conf"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2020.2979517"},{"article-title":"Remote power side-channel attacks on CNN accelerators in FPGAs","year":"2020","author":"moini","key":"ref8"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1145\/3274694.3274696"},{"article-title":"Dynamic channel pruning: Feature boosting and suppression","year":"2019","author":"gao","key":"ref2"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1007\/s11831-019-09344-w"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1145\/3079856.3080254"}],"container-title":["IEEE Computer Architecture Letters"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/10208\/9479861\/09506928.pdf?arnumber=9506928","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,10]],"date-time":"2022-05-10T14:52:21Z","timestamp":1652194341000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9506928\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,7,1]]},"references-count":18,"journal-issue":{"issue":"2"},"URL":"https:\/\/doi.org\/10.1109\/lca.2021.3101505","relation":{},"ISSN":["1556-6056","1556-6064","2473-2575"],"issn-type":[{"type":"print","value":"1556-6056"},{"type":"electronic","value":"1556-6064"},{"type":"electronic","value":"2473-2575"}],"subject":[],"published":{"date-parts":[[2021,7,1]]}}}