8 citations · 11 across the 5 of their papers we have counts for
6 papers
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…
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…
Sampling projections in the uniform norm
David Krieg, Kateryna Pozharska, Mario Ullrich +1
We show that there are sampling projections on arbitrary -dimensional subspaces of with at most samples and norm of order , where is the space of co…
Sampling recovery in and other norms
David Krieg, Kateryna Pozharska, Mario Ullrich +1
We study the recovery of functions in various norms, including with , based on function evaluations. We obtain worst case error bounds for general classes of…
A note on sampling recovery of multivariate functions in the uniform norm
Kateryna Pozharska, Tino Ullrich
We study the recovery of multivariate functions from reproducing kernel Hilbert spaces in the uniform norm. Our main interest is to obtain preasymptotic estimates for the correspon…