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04/20/2023
Optimality of Robust Online Learning
In this paper, we study an online learning algorithm with a robust loss ...
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01/29/2021
Total Stability of SVMs and Localized SVMs
Regularized kernel-based methods such as support vector machines (SVMs) ...
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10/29/2020
On the robustness of kernel-based pairwise learning
It is shown that many results on the statistical robustness of kernel-ba...
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09/22/2017
Total stability of kernel methods
Regularized empirical risk minimization using kernels and their correspo...
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04/15/2016
A short note on extension theorems and their connection to universal consistency in machine learning
Statistical machine learning plays an important role in modern statistic...
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10/12/2015
On the Robustness of Regularized Pairwise Learning Methods Based on Kernels
Regularized empirical risk minimization including support vector machine...
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05/14/2014
Learning rates for the risk of kernel based quantile regression estimators in additive models
Additive models play an important role in semiparametric statistics. Thi...
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01/29/2013
On the Consistency of the Bootstrap Approach for Support Vector Machines and Related Kernel Based Methods
It is shown that bootstrap approximations of support vector machines (SV...
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11/08/2011
On the stability of bootstrap estimators
It is shown that bootstrap approximations of an estimator which is based...
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11/08/2011
Estimation of scale functions to model heteroscedasticity by support vector machines
A main goal of regression is to derive statistical conclusions on the co...
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07/23/2010
Support Vector Machines for Additive Models: Consistency and Robustness
Support vector machines (SVMs) are special kernel based methods and belo...
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12/04/2009