227 citations · 363 across the 18 of their papers we have counts for
4 papers · 1 filter
On the Robustness of Regularized Pairwise Learning Methods Based on Kernels
Andreas Christmann, Ding-Xuan Zhou
Regularized empirical risk minimization including support vector machines plays an important role in machine learning theory. In this paper regularized pairwise learning (RPL) meth…
On the stability of bootstrap estimators
Andreas Christmann, Matias Salibian-Barrera, Stefan Van Aelst
It is shown that bootstrap approximations of an estimator which is based on a continuous operator from the set of Borel probability measures defined on a compact metric space into…
Estimating conditional quantiles with the help of the pinball loss
Ingo Steinwart, Andreas Christmann
The so-called pinball loss for estimating conditional quantiles is a well-known tool in both statistics and machine learning. So far, however, only little work has been done to qua…
Consistency and robustness of kernel-based regression in convex risk minimization
Andreas Christmann, Ingo Steinwart
We investigate statistical properties for a broad class of modern kernel-based regression (KBR) methods. These kernel methods were developed during the last decade and are inspired…