Perturbations, Accuracy and Robustness in Neural Networks

Perturbations, Accuracy and Robustness in Neural Networks

Cesare Alippi (Politecnico Di Milano, Italy) and Giovanni Vanini (Politecnico Di Milano, Italy)
DOI: 10.4018/978-1-59140-553-5.ch402
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Abstract

A robustness analysis for neural networks, namely the evaluation of the effects induced by perturbations affecting the network weights, is a relevant theoretical aspect since weights characterise the “knowledge space” of the neural model and, hence, its inner nature.

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