Andreas Christmann

Orcid: 0000-0002-8408-3549

According to our database1, Andreas Christmann authored at least 30 papers between 1997 and 2024.

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Bibliography

2024
Optimality of Robust Online Learning.
Found. Comput. Math., October, 2024

Bootstrap SGD: Algorithmic Stability and Robustness.
CoRR, 2024

2022
Total Stability of SVMs and Localized SVMs.
J. Mach. Learn. Res., 2022

2020
On the robustness of kernel-based pairwise learning.
CoRR, 2020

2018
Universal consistency and robustness of localized support vector machines.
Neurocomputing, 2018

Total stability of kernel methods.
Neurocomputing, 2018

2016
On the robustness of regularized pairwise learning methods based on kernels.
J. Complex., 2016

A short note on extension theorems and their connection to universal consistency in machine learning.
CoRR, 2016

2013
Robustness Versus Consistency in Ill-Posed Classification and Regression Problems.
Proceedings of the Classification and Data Mining, 2013

On the Consistency of the Bootstrap Approach for Support Vector Machines and Related Kernel-Based Methods.
Proceedings of the Empirical Inference - Festschrift in Honor of Vladimir N. Vapnik, 2013

2012
Consistency of support vector machines using additive kernels for additive models.
Comput. Stat. Data Anal., 2012

2011
On qualitative robustness of support vector machines.
J. Multivar. Anal., 2011

2010
Robustness of reweighted Least Squares Kernel Based Regression.
J. Multivar. Anal., 2010

A review on consistency and robustness properties of support vector machines for heavy-tailed distributions.
Adv. Data Anal. Classif., 2010

Universal Kernels on Non-Standard Input Spaces.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

2009
Fast Learning from Non-i.i.d. Observations.
Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

2008
Bouligand Derivatives and Robustness of Support Vector Machines for Regression.
J. Mach. Learn. Res., 2008

Sparsity of SVMs that use the epsilon-insensitive loss.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008

Support Vector Machines.
Information science and statistics, Springer, ISBN: 978-0-387-77241-7, 2008

2007
A robust estimator for the tail index of Pareto-type distributions.
Comput. Stat. Data Anal., 2007

Robust learning from bites for data mining.
Comput. Stat. Data Anal., 2007

How SVMs can estimate quantiles and the median.
Proceedings of the Advances in Neural Information Processing Systems 20, 2007

2004
On Robustness Properties of Convex Risk Minimization Methods for Pattern Recognition.
J. Mach. Learn. Res., 2004

On a Combination of Convex Risk Minimization Methods.
Proceedings of the Classification, 2004

2003
Robustness against separation and outliers in logistic regression.
Comput. Stat. Data Anal., 2003

Regression depth and support vector machine.
Proceedings of the Data Depth: Robust Multivariate Analysis, 2003

2002
Comparison between various regression depth methods and the support vector machine to approximate the minimum number of misclassifications.
Comput. Stat., 2002

Classification Based on the Support Vector Machine, Regression Depth, and Discriminant Analysis.
Proceedings of the COMPSTAT 2002, 2002

1999
On group sequential tests based on robust location and scale estimators in the two-sample problem.
Comput. Stat., 1999

1997
KIT200x - Eine Expertenumfrage über die Zukunft der Kommunikations- und Informationstechnik jenseits der Jahrtausendwende.
Proceedings of the Struktur und Leistungsspektrum innovativer Rechenzentren, 1997


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