Zobrazeno 1 - 10
of 23
pro vyhledávání: '"Mojan Javaheripi"'
Publikováno v:
ACM Journal on Emerging Technologies in Computing Systems. 19:1-20
We propose AccHashtag , the first framework for high-accuracy detection of fault-injection attacks on Deep Neural Networks (DNNs) with provable bounds on detection performance. Recent literature in fault-injection attacks shows the severe DNN accurac
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8611d73baed29b65cc0515d5e9ec4cc3
https://doi.org/10.1145/3555808
https://doi.org/10.1145/3555808
Publikováno v:
IEEE Journal on Emerging and Selected Topics in Circuits and Systems. 11:611-619
Tensor decomposition is a promising approach for low-power and real-time application of neural networks on resource-constrained embedded devices. This paper proposes AutoRank, an end-to-end framework for customizing neural network decomposition using
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1913adefe3d8ebc2b68a247a11bfb572
https://doi.org/10.1109/jetcas.2021.3127433
https://doi.org/10.1109/jetcas.2021.3127433
Publikováno v:
IEEE Journal on Emerging and Selected Topics in Circuits and Systems. 11:575-585
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::dcf0578388ef17605bbcaa044742a6ea
https://doi.org/10.1109/jetcas.2021.3125309
https://doi.org/10.1109/jetcas.2021.3125309
Publikováno v:
IEEE Design & Test. 38:31-38
Editor’s note: This article describes DeepFense, a framework to make deep learning models automatically and efficiently realizable on constrained devices. — Rosario Cammarota, Intel Labs — Francesco Regazzoni, University of Amsterdam and Univer
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fd03aff49ad3c0c26329d82af130e1d0
https://doi.org/10.1109/mdat.2021.3063344
https://doi.org/10.1109/mdat.2021.3063344
Publikováno v:
IEEE Transactions on Dependable and Secure Computing. 18:736-752
Recent advances in adversarial Deep Learning (DL) have opened up a new and largely unexplored surface for malicious attacks jeopardizing the integrity of autonomous DL systems. This article introduces CuRTAIL, a novel end-to-end computing framework t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8701d70cea9dfe9c9619063ae385d99d
https://doi.org/10.1109/tdsc.2020.3024191
https://doi.org/10.1109/tdsc.2020.3024191
Autor:
Mehran Abbasi Shirsavar, Mehrnoosh Taghavimehr, Lionel J. Ouedraogo, Mojan Javaheripi, Nicole N. Hashemi, Farinaz Koushanfar, Reza Montazami
Publikováno v:
Biosensorsbioelectronics. 212
Electrohydrodynamic-jet (E-jet) printing technique enables the high-resolution printing of complex soft electronic devices. As such, it has an unmatched potential for becoming the conventional technique for printing soft electronic devices. In this s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ea1908942a050ec1c4c75cb6db47d0fc
https://pubmed.ncbi.nlm.nih.gov/35671690
https://pubmed.ncbi.nlm.nih.gov/35671690
Video compression plays a crucial role in video streaming and classification systems by maximizing the end-user quality of experience (QoE) at a given bandwidth budget. In this paper, we conduct the first systematic study for adversarial attacks on d
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6e05d189793ebb95fe34b79397332b7d
http://arxiv.org/abs/2203.10183
http://arxiv.org/abs/2203.10183
Publikováno v:
ACM Transactions on Embedded Computing Systems. 19:1-29
This article proposes EncoDeep, an end-to-end framework that facilitates encoding, bitwidth customization, fine-tuning, and implementation of neural networks on FPGA platforms. EncoDeep incorporates nonlinear encoding to the computation flow of neura
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::eabd75b6f19fcdaa1cabcbf24d34ba5e
https://doi.org/10.1145/3391901
https://doi.org/10.1145/3391901
Publikováno v:
IEEE Journal of Selected Topics in Signal Processing. 14:750-764
This paper introduces an adaptive sampling methodology for automated compression of Deep Neural Networks (DNNs) for accelerated inference on resource-constrained platforms. Modern DNN compression techniques comprise various hyperparameters that requi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::959c12abda2f2051a18131fb35841a0d
https://doi.org/10.1109/jstsp.2020.2992384
https://doi.org/10.1109/jstsp.2020.2992384
Publikováno v:
CCS
We introduce COINN - an efficient, accurate, and scalable framework for oblivious deep neural network (DNN) inference in the two-party setting. In our system, DNN inference is performed without revealing the client's private inputs to the server or r
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::766af66379a3e7fc9fcab80b13f9f1d0
https://doi.org/10.1145/3460120.3484797
https://doi.org/10.1145/3460120.3484797