Correction to: Parseval Proximal Neural Networks
نویسندگان
چکیده
منابع مشابه
Parseval Networks: Improving Robustness to Adversarial Examples
We introduce Parseval networks, a form of deep neural networks in which the Lipschitz constant of linear, convolutional and aggregation layers is constrained to be smaller than 1. Parseval networks are empirically and theoretically motivated by an analysis of the robustness of the predictions made by deep neural networks when their input is subject to an adversarial perturbation. The most impor...
متن کاملParseval Networks: Improving Robustness to Adversarial Examples
We introduce Parseval networks, a form of deep neural networks in which the Lipschitz constant of linear, convolutional and aggregation layers is constrained to be smaller than 1. Parseval networks are empirically and theoretically motivated by an analysis of the robustness of the predictions made by deep neural networks when their input is subject to an adversarial perturbation. The most impor...
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Correction to "Linear and Logarithmic Capacities in Associative Neural Networks"
J. Ma, J. Wu, and Q. Cheng kindly pointed out that [1, Proof of Proposition 1(b)] contains an overcount. The statement of the proposition reads: Let n be the family of bases for with all basis elements constrained to be binary n-tuples; (i.e., E = fe1; e2; . . . ; eng 2 n if, and only if, e1, e2; . . . ; en 2 f 1;+1g are linearly independent [over the field of the reals]). Then, asymptotically ...
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ژورنال
عنوان ژورنال: Journal of Fourier Analysis and Applications
سال: 2021
ISSN: 1069-5869,1531-5851
DOI: 10.1007/s00041-021-09848-9