2 citations · 4 across the 12 of their papers we have counts for
3 papers · 1 filter
Step-Size Stability in Stochastic Optimization: A Theoretical Perspective
Fabian Schaipp, Robert M. Gower, Adrien Taylor
We present a theoretical analysis of stochastic optimization methods in terms of their sensitivity with respect to the step size. We identify a key quantity that, for each method,…
A Stochastic Proximal Polyak Step Size
Fabian Schaipp, Robert M. Gower, Michael Ulbrich
Recently, the stochastic Polyak step size (SPS) has emerged as a competitive adaptive step size scheme for stochastic gradient descent. Here we develop ProxSPS, a proximal variant…
A Semismooth Newton Stochastic Proximal Point Algorithm with Variance Reduction
Andre Milzarek, Fabian Schaipp, Michael Ulbrich
We develop an implementable stochastic proximal point (SPP) method for a class of weakly convex, composite optimization problems. The proposed stochastic proximal point algorithm i…