Talha Cihad Gülcü

Stronger convergence results for deep residual networks: network width scales linearly with training data size

2020 · Information and Inference A Journal of the IMA

Abstract 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 the optimization process crucially depends on the characteristics of …