3 papers
math.ST2026
Higher-order spectral perturbation expansions II: Kernel matrices and manifold learning
Bernhard Stankewitz, Martin Wahl
We study spectral concentration bounds for kernel matrices as approximation of the corresponding kernel integral operator. Results are established under weak assumptions on the dat…
cs.LG2025
Provable Mixed-Noise Learning with Flow-Matching
Paul Hagemann, Robert Gruhlke, Bernhard Stankewitz +2
We study Bayesian inverse problems with mixed noise, modeled as a combination of additive and multiplicative Gaussian components. While traditional inference methods often assume f…
stat.ML2025
EarlyStopping: Implicit Regularization for Iterative Learning Procedures in Python
Eric Ziebell, Ratmir Miftachov, Bernhard Stankewitz +1
Iterative learning procedures are ubiquitous in machine learning and modern statistics. Regularision is typically required to prevent inflating the expected loss of a procedure in…