Fabian Schaipp

Orcid: 0000-0002-0673-9944

According to our database1, Fabian Schaipp authored at least 13 papers between 2020 and 2026.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

On csauthors.net:

Bibliography

2026
Step-Size Stability in Stochastic Optimization: A Theoretical Perspective.
CoRR, February, 2026

2025
Optimization Benchmark for Diffusion Models on Dynamical Systems.
CoRR, October, 2025

Analysis of an Idealized Stochastic Polyak Method and its Application to Black-Box Model Distillation.
CoRR, April, 2025

Tracking the Median of Gradients with a Stochastic Proximal Point Method.
Trans. Mach. Learn. Res., 2025

The Surprising Agreement Between Convex Optimization Theory and Learning-Rate Scheduling for Large Model Training.
Proceedings of the Forty-second International Conference on Machine Learning, 2025

2024
A Semismooth Newton Stochastic Proximal Point Algorithm with Variance Reduction.
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)
PhD thesis, 2024

SGD with Clipping is Secretly Estimating the Median Gradient.
CoRR, 2024

MoMo: Momentum Models for Adaptive Learning Rates.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023
A Stochastic Proximal Polyak Step Size.
Trans. Mach. Learn. Res., 2023

Function Value Learning: Adaptive Learning Rates Based on the Polyak Stepsize and Function Splitting in ERM.
CoRR, 2023

2021
GGLasso - a Python package for General Graphical Lasso computation.
J. Open Source Softw., 2021

2020
Simulation vs. Testbed: Small Scale Experimental Validation of an Open-Source LTE-A Model.
Proceedings of the 31st IEEE Annual International Symposium on Personal, 2020


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