3 papers
math.ST2020
On the robustness of minimum norm interpolators and regularized empirical risk minimizers
Geoffrey Chinot, Matthias Löffler, Sara van de Geer
This article develops a general theory for minimum norm interpolating estimators and regularized empirical risk minimizers (RERM) in linear models in the presence of additive, pote…
stat.ML2018
A Framework for the construction of upper bounds on the number of affine linear regions of ReLU feed-forward neural networks
Peter Hinz, Sara van de Geer
We present a framework to derive upper bounds on the number of regions that feed-forward neural networks with ReLU activation functions are affine linear on. It is based on an indu…
math.ST2018
Sharp oracle inequalities for stationary points of nonconvex penalized M-estimators
Andreas Elsener, Sara van de Geer
Many statistical estimation procedures lead to nonconvex optimization problems. Algorithms to solve these are often guaranteed to output a stationary point of the optimization prob…