76 citations · 343 across the 42 of their papers we have counts for
55 papers
A sharp bound for sampling widths in the uniform norm: kernel -optimal designs and oversampling
Sebastian Neumayer, Tino Ullrich
For every reproducing kernel Hilbert space with bounded kernel , we prove that the linear sampling widths and Gelfand widths in the unif…
Greedy sampling designs via reduced basis methods: optimal recovery in the uniform norm
Sebastian Neumayer, Kateryna Pozharska, Tino Ullrich
We study optimal sampling recovery in reproducing kernel Hilbert spaces (RKHS) in the uniform norm. For every RKHS with bounded kernel, we establish new comparisons between linear…
Best -term trigonometric approximation in weighted Wiener spaces and applications
Moritz Moeller, Serhii Stasyuk, Tino Ullrich
In this paper we study best \(m\)-term trigonometric approximation in weighted Wiener spaces and its consequences for Besov and Sobolev spaces with bounded mixed derivative/differe…
High-dimensional sparse recovery from function samples Decoders, guarantees and instance optimality
Moritz Moeller, Sebastian Neumayer, Kateryna Pozharska +2
We investigate the reconstruction of multivariate functions from samples using sparse recovery techniques. For Square Root Lasso, Orthogonal Matching Pursuit, and Compressive Sampl…
Exact discretization, tight frames and recovery via D-optimal designs
Felix Bartel, Lutz Kämmerer, Kateryna Pozharska +2
-optimal designs originate in statistics literature as an approach for optimal experimental designs. In numerical analysis points and weights resulting from maximal determinants…
High-dimensional sparse trigonometric approximation in the uniform norm and consequences for sampling recovery
Moritz Moeller, Serhii Stasyuk, Tino Ullrich
Recent findings by Jahn, T. Ullrich, Voigtlaender [14] relate non-linear sampling numbers for the square norm to quantities involving trigonometric best term approximation erro…