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Robust Machine Learning Systems: Challenges,Current Trends, Perspectives, and the Road Ahead

Title
Robust Machine Learning Systems: Challenges,Current Trends, Perspectives, and the Road Ahead
Author
최정욱
Keywords
Training data; Artificial neural networks; Reliability; Smart devices; Hardware; Machine learning
Issue Date
2020-04
Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Citation
IEEE DESIGN & TEST, v. 37, no. 2, page. 30-57
Abstract
Currently, machine learning (ML) techniques are at the heart of smart cyber-physical systems (CPS) and Internet-of-Things (IoT). This article discusses various challenges and probable solutions for security attacks on these ML-inspired hardware and software techniques. -Partha Pratim Pande, Washington State University
URI
https://ieeexplore.ieee.org/document/8979377https://repository.hanyang.ac.kr/handle/20.500.11754/166153
ISSN
2168-2356; 2168-2364
DOI
10.1109/MDAT.2020.2971217
Appears in Collections:
COLLEGE OF ENGINEERING[S](공과대학) > ELECTRONIC ENGINEERING(융합전자공학부) > Articles
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