97 citations · 132 across the 6 of their papers we have counts for
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quant-ph2020★ 11 cited
Defence against adversarial attacks using classical and quantum-enhanced Boltzmann machines
Aidan Kehoe, Peter Wittek, Yanbo Xue +1
We provide a robust defence to adversarial attacks on discriminative algorithms. Neural networks are naturally vulnerable to small, tailored perturbations in the input data that le…
cs.DC2020★ 97 cited
Distributed Training of Deep Learning Models: A Taxonomic Perspective
Matthias Langer, Zhen He, Wenny Rahayu +1
Distributed deep learning systems (DDLS) train deep neural network models by utilizing the distributed resources of a cluster. Developers of DDLS are required to make many decision…