3 papers
math.NA2026
Convergence for adaptive resampling of random Fourier features
Xin Huang, Aku Kammonen, Anamika Pandey +4
The machine learning random Fourier feature method for data in high dimension is computationally and theoretically attractive since the optimization is based on a convex standard l…
cs.LG2025
An Adaptive Random Fourier Features approach Applied to Learning Stochastic Differential Equations
Owen Douglas, Aku Kammonen, Anamika Pandey +1
This work proposes a training algorithm based on adaptive random Fourier features (ARFF) with Metropolis sampling and resampling \cite{kammonen2024adaptiverandomfourierfeatures} fo…
cs.LG2025
Adaptive Random Fourier Features Training Stabilized By Resampling With Applications in Image Regression
Aku Kammonen, Anamika Pandey, Erik von Schwerin +1
This paper presents an enhanced adaptive random Fourier features (ARFF) training algorithm for shallow neural networks, building upon the work introduced in "Adaptive Random Fourie…