L. Kämmerer

collaborators

4 papers

math.NA2020

Sparse Fourier Transforms on Rank-1 Lattices for the Rapid and Low-Memory Approximation of Functions of Many Variables

Craig Gross, Mark Iwen, Lutz Kämmerer +1

We consider fast, provably accurate algorithms for approximating functions on the $d$ -dimensional torus, $f : T^{d} \to C$ , that are sparse (or compressibl…

math.NA2019

Worst-case recovery guarantees for least squares approximation using random samples

Lutz Kämmerer, Tino Ullrich, Toni Volkmer

We construct a least squares approximation method for the recovery of complex-valued functions from a reproducing kernel Hilbert space on $D \subset R^{d}$ . The nodes are dr…

math.NA2019

Multiple Lattice Rules for Multivariate $L_{\infty}$ Approximation in the Worst-Case Setting

Lutz Kämmerer

We develop a general framework for estimating the $L_{\infty} (T^{d})$ error for the approximation of multivariate periodic functions belonging to specific reproducing kernel H…

math.NA2019

A sparse FFT approach for ODE with random coefficients

Maximilian Bochmann, Lutz Kämmerer, Daniel Potts

The paper presents a general strategy to solve ordinary differential equations (ODE), where some coefficient depend on the spatial variable and on additional random variables. The…

Sparse Fourier Transforms on Rank-1 Lattices for the Rapid and Low-Memory Approximation of Functions of Many Variables

Worst-case recovery guarantees for least squares approximation using random samples

Multiple Lattice Rules for Multivariate L∞​ Approximation in the Worst-Case Setting

A sparse FFT approach for ODE with random coefficients

Multiple Lattice Rules for Multivariate $L_{\infty}$ Approximation in the Worst-Case Setting