2 papers
cs.LG2024
Dimension-independent learning rates for high-dimensional classification problems
Andres Felipe Lerma-Pineda, Philipp Petersen, Simon Frieder +1
We study the problem of approximating and estimating classification functions that have their decision boundary in the space. Functions of type arise naturally as s…
math.NA2022
Deep neural networks can stably solve high-dimensional, noisy, non-linear inverse problems
Andrés Felipe Lerma Pineda, Philipp Christian Petersen
We study the problem of reconstructing solutions of inverse problems when only noisy measurements are available. We assume that the problem can be modeled with an infinite-dimensio…