4 citations · 9 across the 7 of their papers we have counts for
7 papers
Practical Tikhonov Regularized Estimators in Reproducing Kernel Hilbert Spaces for Statistical Inverse Problems
Robert Hable
Regularized kernel methods such as support vector machines (SVM) and support vector regression (SVR) constitute a broad and flexible class of methods which are theoretically well i…
On the Consistency of the Bootstrap Approach for Support Vector Machines and Related Kernel Based Methods
Andreas Christmann, Robert Hable
It is shown that bootstrap approximations of support vector machines (SVMs) based on a general convex and smooth loss function and on a general kernel are consistent. This result i…
Asymptotic Confidence Sets for General Nonparametric Regression and Classification by Regularized Kernel Methods
Robert Hable
Regularized kernel methods such as, e.g., support vector machines and least-squares support vector regression constitute an important class of standard learning algorithms in machi…
Estimation of scale functions to model heteroscedasticity by support vector machines
Robert Hable, Andreas Christmann
A main goal of regression is to derive statistical conclusions on the conditional distribution of the output variable Y given the input values x. Two of the most important characte…
Asymptotic Normality of Support Vector Machine Variants and Other Regularized Kernel Methods
Robert Hable
In nonparametric classification and regression problems, regularized kernel methods, in particular support vector machines, attract much attention in theoretical and in applied sta…
Support Vector Machines for Additive Models: Consistency and Robustness
Andreas Christmann, Robert Hable
Support vector machines (SVMs) are special kernel based methods and belong to the most successful learning methods since more than a decade. SVMs can informally be described as a k…
Qualitative Robustness of Support Vector Machines
Robert Hable, Andreas Christmann
Support vector machines have attracted much attention in theoretical and in applied statistics. Main topics of recent interest are consistency, learning rates and robustness. In th…