3 papers
math.LO2026
Fast approximation and learning of binary classification tasks in o-minimal structures using ReLU neural networks
Clemens Kinn, Philipp Petersen
We study binary classification problems whose decision sets are given by definable sets in o-minimal expansions of the real field. Motivated by cell decomposition of definable sets…
stat.ML2026
Minimax learning rates for estimating binary classifiers under margin conditions
Jonathan GarcÃa, Philipp Petersen
We study classification problems using binary estimators where the decision boundary is described by horizon functions and where the data distribution satisfies a geometric margin…
cs.LG2025
High-dimensional classification problems with Barron regular boundaries under margin conditions
Jonathan GarcÃa, Philipp Petersen
We prove that a classifier with a Barron-regular decision boundary can be approximated with a rate of high polynomial degree by ReLU neural networks with three hidden layers when a…