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stat.ML2024★ 1 cited
Analysis of the rate of convergence of an over-parametrized convolutional neural network image classifier learned by gradient descent
Michael Kohler, Adam Krzyzak, Benjamin Walter
Image classification based on over-parametrized convolutional neural networks with a global average-pooling layer is considered. The weights of the network are learned by gradient…
math.ST2024
Learning of deep convolutional network image classifiers via stochastic gradient descent and over-parametrization
Michael Kohler, Adam Krzyzak, Alisha Sänger
Image classification from independent and identically distributed random variables is considered. Image classifiers are defined which are based on a linear combination of deep conv…