In this article, we consider convergence of stochastic gradient descent schemes (SGD),
including momentum stochastic gradient descent (MSGD), under weak assumptions on the …

Ensemble Kalman inversion (EKI) is an ensemble-based method to solve inverse problems.
Its gradient-free formulation makes it an attractive tool for problems with involved …

In this work, we consider the convergence of Polyak's heavy ball method, both in continuous
and discrete time, on a non-convex objective function. We recover the convergence rates …

We propose a novel time window-based analysis technique to investigate the convergence
properties of the stochastic gradient descent method with momentum (SGDM) in nonconvex …

Stochastic gradient descent (SGD) has been a go-to algorithm for nonconvex stochastic
optimization problems arising in machine learning. Its theory however often requires a …

This work addresses the convergence behaviour of first-order optimization methods in the
context of reinforcement learning. Specifically, we analyse the vanilla Policy Gradient (PG) …