Andreas Christmann

According to our database, Andreas Christmann authored at least 29 papers between 1997 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2023

Optimality of Robust Online Learning.

Zheng-Chu Guo, Andreas Christmann, Lei Shi

CoRR, 2023

2022

Total Stability of SVMs and Localized SVMs.

Hannes Köhler, Andreas Christmann

J. Mach. Learn. Res., 2022

2020

On the robustness of kernel-based pairwise learning.

Patrick Gensler, Andreas Christmann

CoRR, 2020

2018

Universal consistency and robustness of localized support vector machines.

Florian Dumpert, Andreas Christmann

Neurocomputing, 2018

Total stability of kernel methods.

Andreas Christmann, Dao-Hong Xiang, Ding-Xuan Zhou

Neurocomputing, 2018

2016

On the robustness of regularized pairwise learning methods based on kernels.

Andreas Christmann, Ding-Xuan Zhou

J. Complex., 2016

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

Andreas Christmann, Florian Dumpert, Dao-Hong Xiang

CoRR, 2016

2013

Robustness Versus Consistency in Ill-Posed Classification and Regression Problems.

Robert Hable, Andreas Christmann

Proceedings of the Classification and Data Mining, 2013

On the Consistency of the Bootstrap Approach for Support Vector Machines and Related Kernel-Based Methods.

Andreas Christmann, Robert Hable

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.

Andreas Christmann, Robert Hable

Comput. Stat. Data Anal., 2012

2011

On qualitative robustness of support vector machines.

Robert Hable, Andreas Christmann

J. Multivar. Anal., 2011

2010

Robustness of reweighted Least Squares Kernel Based Regression.

Michiel Debruyne, Andreas Christmann, Mia Hubert, Johan A. K. Suykens

J. Multivar. Anal., 2010

A review on consistency and robustness properties of support vector machines for heavy-tailed distributions.

Arnout Van Messem, Andreas Christmann

Adv. Data Anal. Classif., 2010

Universal Kernels on Non-Standard Input Spaces.

Andreas Christmann, Ingo Steinwart

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.

Ingo Steinwart, Andreas Christmann

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.

Andreas Christmann, Arnout Van Messem

J. Mach. Learn. Res., 2008

Sparsity of SVMs that use the epsilon-insensitive loss.

Ingo Steinwart, Andreas Christmann

Proceedings of the Advances in Neural Information Processing Systems 21, 2008

Support Vector Machines.

Ingo Steinwart, Andreas Christmann

Information science and statistics, Springer, ISBN: 978-0-387-77241-7, 2008

2007

A robust estimator for the tail index of Pareto-type distributions.

B. Vandewalle, Jan Beirlant, Andreas Christmann, Mia Hubert

Comput. Stat. Data Anal., 2007

Robust learning from bites for data mining.

Andreas Christmann, Ingo Steinwart, Mia Hubert

Comput. Stat. Data Anal., 2007

How SVMs can estimate quantiles and the median.

Andreas Christmann, Ingo Steinwart

Proceedings of the Advances in Neural Information Processing Systems 20, 2007

2004

On Robustness Properties of Convex Risk Minimization Methods for Pattern Recognition.

Andreas Christmann, Ingo Steinwart

J. Mach. Learn. Res., 2004

On a Combination of Convex Risk Minimization Methods.

Andreas Christmann

Proceedings of the Classification, 2004

2003

Robustness against separation and outliers in logistic regression.

Peter J. Rousseeuw, Andreas Christmann

Comput. Stat. Data Anal., 2003

Regression depth and support vector machine.

Andreas Christmann

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.

Andreas Christmann, Paul Fischer, Thorsten Joachims

Comput. Stat., 2002

Classification Based on the Support Vector Machine, Regression Depth, and Discriminant Analysis.

Andreas Christmann, Paul Fischer, Thorsten Joachims

Proceedings of the COMPSTAT 2002, 2002

1999

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

Andreas Christmann

Comput. Stat., 1999

1997

KIT200x - Eine Expertenumfrage über die Zukunft der Kommunikations- und Informationstechnik jenseits der Jahrtausendwende.

Andreas Christmann, Günter Schwichtenberg

Proceedings of the Struktur und Leistungsspektrum innovativer Rechenzentren, 1997