activity
20202025
most citedStochastic Gradient Descent in Hilbert Scales: Smoothness, Preconditioning and Earlier Stopping

2 citations · 2 across the 3 of their papers we have counts for

collaborators

3 papers

math.SP2025

Weyl asymptotics for pseudodifferential operators in a discrete setting

Markus Klein, Enrico Reiss, Elke Rosenberger

We prove a sharp Weyl estimate for the number of eigenvalues belonging to a fixed interval of energy of a self-adjoint difference operator acting on if the…

stat.ML2021

Data splitting improves statistical performance in overparametrized regimes

Nicole Mücke, Enrico Reiss, Jonas Rungenhagen +1

While large training datasets generally offer improvement in model performance, the training process becomes computationally expensive and time consuming. Distributed learning is a…

stat.ML2020★ 2 cited

Stochastic Gradient Descent in Hilbert Scales: Smoothness, Preconditioning and Earlier Stopping

Nicole Mücke, Enrico Reiss

Stochastic Gradient Descent (SGD) has become the method of choice for solving a broad range of machine learning problems. However, some of its learning properties are still not ful…