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Machine Learning Systems in the IoT: Trustworthiness Trade-offs for Edge
  Intelligence

Machine Learning Systems in the IoT: Trustworthiness Trade-offs for Edge Intelligence

1 December 2020
Wiebke Toussaint
Aaron Yi Ding
ArXivPDFHTML

Papers citing "Machine Learning Systems in the IoT: Trustworthiness Trade-offs for Edge Intelligence"

5 / 5 papers shown
Title
Towards Trustworthy Edge Intelligence: Insights from Voice-Activated
  Services
Towards Trustworthy Edge Intelligence: Insights from Voice-Activated Services
W. Hutiri
Aaron Yi Ding
30
4
0
20 Jun 2022
Revisiting the Arguments for Edge Computing Research
Revisiting the Arguments for Edge Computing Research
Blesson Varghese
E. de Lara
Aaron Yi Ding
Cheol-Ho Hong
F. Bonomi
...
P. Harvey
P. Hewkin
Weisong Shi
M. Thiele
P. Willis
28
29
0
23 Jun 2021
Benchmarking TinyML Systems: Challenges and Direction
Benchmarking TinyML Systems: Challenges and Direction
Colby R. Banbury
Vijay Janapa Reddi
Max Lam
William Fu
A. Fazel
...
Jae-sun Seo
Jeff Sieracki
Urmish Thakker
Marian Verhelst
Poonam Yadav
109
228
0
10 Mar 2020
What is the State of Neural Network Pruning?
What is the State of Neural Network Pruning?
Davis W. Blalock
Jose Javier Gonzalez Ortiz
Jonathan Frankle
John Guttag
191
1,027
0
06 Mar 2020
Model-Reuse Attacks on Deep Learning Systems
Model-Reuse Attacks on Deep Learning Systems
Yujie Ji
Xinyang Zhang
S. Ji
Xiapu Luo
Ting Wang
SILM
AAML
134
186
0
02 Dec 2018
1