Fabian Schaipp

According to our database, Fabian Schaipp authored at least 8 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

A Semismooth Newton Stochastic Proximal Point Algorithm with Variance Reduction.

Andre Milzarek, Fabian Schaipp, Michael Ulbrich

SIAM J. Optim., March, 2024

Topics in Stochastic Optimization: Learning with Implicit and Adaptive Steps (Implizite und Adaptive Methoden der Stochastischen Optimierung für Machine Learning)

Fabian Schaipp

PhD thesis, 2024

SGD with Clipping is Secretly Estimating the Median Gradient.

Fabian Schaipp, Guillaume Garrigos, Umut Simsekli, Robert M. Gower

CoRR, 2024

MoMo: Momentum Models for Adaptive Learning Rates.

Fabian Schaipp, Ruben Ohana, Michael Eickenberg, Aaron Defazio, Robert M. Gower

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

A Stochastic Proximal Polyak Step Size.

Fabian Schaipp, Robert M. Gower, Michael Ulbrich

Trans. Mach. Learn. Res., 2023

Function Value Learning: Adaptive Learning Rates Based on the Polyak Stepsize and Function Splitting in ERM.

Guillaume Garrigos, Robert M. Gower, Fabian Schaipp

CoRR, 2023

2021

GGLasso - a Python package for General Graphical Lasso computation.

Fabian Schaipp, Oleg Vlasovets, Christian Müller

J. Open Source Softw., 2021

2020

Simulation vs. Testbed: Small Scale Experimental Validation of an Open-Source LTE-A Model.

Lars Wischhof, Fabian Schaipp, Stefan Schuhbäck, Gerta Köster

Proceedings of the 31st IEEE Annual International Symposium on Personal, 2020