Taming neural networks with TUSLA: Non-convex learning via adaptive stochastic gradient Langevin algorithms

Attila Lovas, Iosif Lytras, Miklós Rásonyi +1

Artificial neural networks (ANNs) are typically highly nonlinear systems which are finely tuned via the optimization of their associated, non-convex loss functions. In many cases,…