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stat.ML2019
Stronger Convergence Results for Deep Residual Networks: Network Width Scales Linearly with Training Data Size
Talha Cihad Gulcu
Deep neural networks are highly expressive machine learning models with the ability to interpolate arbitrary datasets. Deep nets are typically optimized via first-order methods and…
stat.ML2019
Comments on "Deep Neural Networks with Random Gaussian Weights: A Universal Classification Strategy?"
Talha Cihad Gulcu, Alper Gungor
In a recently published paper [1], it is shown that deep neural networks (DNNs) with random Gaussian weights preserve the metric structure of the data, with the property that the d…