Benchmarking Adversarial Robustness of Compressed Deep Learning Models

The increasing size of Deep Neural Networks (DNNs) poses a pressing need for model compression, particularly when employed on resource constrained devices. Concurrently, the susceptibility of DNNs to adversarial attacks presents another significant hurdle. Despite substantial research on both model...

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Veröffentlicht in:	arXiv.org 2023-08
Hauptverfasser:	Vora, Brijesh, Patwari, Kartik, Hafiz, Syed Mahbub, Shafiq, Zubair, Chen-Nee, Chuah
Format:	Artikel
Sprache:	eng
Schlagworte:	Artificial neural networks Machine learning Pruning Robustness
Online-Zugang:	Volltext
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