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RoHNAS: A Neural Architecture Search Framework with Conjoint
  Optimization for Adversarial Robustness and Hardware Efficiency of
  Convolutional and Capsule Networks

RoHNAS: A Neural Architecture Search Framework with Conjoint Optimization for Adversarial Robustness and Hardware Efficiency of Convolutional and Capsule Networks

11 October 2022
Alberto Marchisio
Vojtěch Mrázek
Andrea Massa
Beatrice Bussolino
Maurizio Martina
Muhammad Shafique
    AAML
ArXivPDFHTML

Papers citing "RoHNAS: A Neural Architecture Search Framework with Conjoint Optimization for Adversarial Robustness and Hardware Efficiency of Convolutional and Capsule Networks"

4 / 4 papers shown
Title
A Comprehensive Survey of Convolutions in Deep Learning: Applications,
  Challenges, and Future Trends
A Comprehensive Survey of Convolutions in Deep Learning: Applications, Challenges, and Future Trends
Abolfazl Younesi
Mohsen Ansari
Mohammadamin Fazli
A. Ejlali
Muhammad Shafique
Joerg Henkel
3DV
33
43
0
23 Feb 2024
Robust Machine Learning Systems: Challenges, Current Trends,
  Perspectives, and the Road Ahead
Robust Machine Learning Systems: Challenges, Current Trends, Perspectives, and the Road Ahead
Muhammad Shafique
Mahum Naseer
T. Theocharides
C. Kyrkou
O. Mutlu
Lois Orosa
Jungwook Choi
OOD
63
100
0
04 Jan 2021
Neural Architecture Search with Reinforcement Learning
Neural Architecture Search with Reinforcement Learning
Barret Zoph
Quoc V. Le
264
5,290
0
05 Nov 2016
Adversarial examples in the physical world
Adversarial examples in the physical world
Alexey Kurakin
Ian Goodfellow
Samy Bengio
SILM
AAML
247
5,813
0
08 Jul 2016
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