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Accuracy-Robustness Trade-Off For Positively Weighted Neural Networks
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Accuracy-Robustness Trade-Off For Positively Weighted Neural Networks
This work proposes a new learning strategy for training a feedforward neural network subject to spectral norm and nonnegativity constraints. Our primary goal is to control the Lipschitz constant of the network in order to make it robust against adversaria
This work proposes a new learning strategy for training a feedforward neural network subject to spectral norm and nonnegativity constraints. Our primary goal is to control the Lipschitz constant of the network in order to make it robust against adversaria
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