Andreas Christmann
Professor of Stochastics (Head)  

     Research         Publications      Presentations
     Projects      Software      Teaching
     How to reach me      CV      Links

 

RESEARCH TOPICS

  • Mathematical statistics and applications
  • Nonparametrical statistics
  • Statistical machine learning theory, empirical risk minimization
  • Support Vector Machines
  • Computational statistics
  • Robust statistics
  • Actuarial statistics and finance
  • Data Mining
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BOOKS

  • Support Vector Machines
    Steinwart, I., Christmann, A. (2008).
    Springer, New York.
         Link to Book Website

  • Data Mining und Statistik in Hochschulen und Wirtschaft. Proceedings der 6. Konferenz der SAS®-Anwender in Forschung und Entwicklung (KSFE).
    Eds.: Christmann, A., Weihs, C. (2003).
    Shaker-Verlag Aachen
    Link to Publisher Website

RECENT PUBLICATIONS

  • Consistency of support vector machines using additive kernels for additive models .
    Christmann, A., Hable, R. (2012).
    Computational Statistics & Data Analysis, 56, 854 - 873.

  • On the Stability of Bootstrap Estimators.
    Christmann, A., Salibian-Barrera, M., Van Aelst, S. (2011).
    PDF, arXiv

  • Estimation of scale functions to model heteroscedasticity by support vector machines.
    Hable, R., Christmann, A. (2011).
    PDF, arXiv

  • On qualitative robustness of support vector machines.
    Hable, R., Christmann, A. (2011).
    Journal of Multivariate Analysis, 102, 993-1007.
    PDF, arXiv

  • Estimating Conditional Quantiles with the Help of the Pinball Loss
    Steinwart, I., Christmann, A. (2011).
    Bernoulli, 17, 211-225.
    PDF, arXiv Link to Bernoulli Journal

  • Support Vector Machines for Additive Models: Consistency and Robustness.
    Christmann, A. and Hable, R. (2011).
    Accepted: Computational Statistics and Data Analysis.
    PDF, arXiv

  • Universal Kernels on Non-Standard Input Spaces.
    Christmann, A. and Steinwart, I., (2010).
    Advances in Neural Information Processing Systems, 23, 406-414.
    PDF

  • A Review on Consistency and Robustness Properties of Support Vector Machines for Heavy-Tailed Distributions.
    Van Messem, A. and Christmann, A. (2010).
    Advances in Data Analysis and Classification, 4, 199-220.

  • Robustness of Reweighted Least Squares Kernel Based Regression.
    Debruyne, M., Christmann, A., Hubert, M., Suykens, J.A.K. (2010).
    Journal of Multivariate Analysis, 101, 447-463.
    PDF (preprint)

  • On the interface of statistics and machine learning.
    Christmann, A., Shen, X., editors. (2009).
    Special issue: Statistics and Its Interface, 2 (3).
    Link to Journal Website

  • Fast Learning from Non-i.i.d. Observations.
    Steinwart, I., Christmann, A. (2009).
    Advances in Neural Information Processing Systems, 22, 1768-1776.
    PDF

  • On Consistency and Robustness Properties of Support Vector Machines for Heavy-Tailed Distributions
    Christmann, A., Van Messem, A., Steinwart, I. (2009).
    Statistics and Its Interface, 2, 311-327.
        PDF

  • Sparsity of SVMs that use the epsilon-insensitive loss
    Steinwart, I., Christmann, A. (2009).
    Advances in Neural Information Processing Systems, 21, pages 1569--1576, eds. D. Koller, D. Schuurmans, Y. Bengio, and L. Bottou.
    PDF

  • How Support Vector Machines can estimate quantiles and the median.
    Steinwart, I., Christmann, A. (2008).
    Advances in Neural Information Processing Systems, 20, pages 305-312, eds. J.C. Platt, D. Koller, Y. Singer, and S. Roweis, MIT Press, Cambridge, MA.
    PDF

  • Bouligand derivatives and robustness of support vector machines for regression.
    Christmann, A. and Van Messem, A. (2008). Journal of Machine Learning Research, 9, 915-936.
        PDF  •  Link to Journal

  • Consistency of kernel based quantile regression.
    Christmann, A. and Steinwart, I. (2008).
    Applied Stochastic Models in Business and Industry (Wiley), 24(2), 171-183.
        PDF  •  Link to Journal

  • Consistency and robustness of kernel based regression.
    Christmann, A. and Steinwart, I. (2007).
    Bernoulli 13(3), 799-819.
         PDF  •  Link to Journal

  • Robust Learning From Bites for Data Mining.
    Christmann, A., Steinwart, I., and Hubert, M. (2007).
    Computational Statistics and Data Analysis, 52, 347-361.
        (available online at www.sciencedirect.com)
        PDF (Preprint)

  • A Robust Estimator for the Tail Index of Pareto-type Distributions.
    B. Vandewalle, J. Beirlant, A. Christmann, M. Hubert (2007).
    Computational Statistics and Data Analysis, 51, 6252-6268.
        (available online at www.sciencedirect.com)
        PDF (Preprint)

  • Robust estimation of Cronbach's alpha.
    Christmann, A. and Van Aelst, S. (2006).
    Journal of Multivariate Analysis, 97, 1660-1674.
        (available online at www.sciencedirect.com)
        PDF

  • Regression depth and support vector machine..
    Christmann, A. (2006). American Mathematical Society, DIMACS Series in Discrete Mathematics and Theoretical Computer Science, Vol. 72, 71-85.
        PDF (Preprint)

  • Angiographic Follow-Up After Carotid Artery Stenting of Bifurcation Stenosis..
    Hauth, E.A., Jansen, C., Drescher, R., Schwarz, M., Christmann, A., Jaeger, H., Forsting, M., Mathias, K. (2006).
    Fortschritte auf dem Gebiet der Röntgenstrahlen und der bildgebenden Verfahren, 178, 787-793.

  • Analysis of Surgical Management of Calvarial Tumours and First Results of a Newly Designed Robotic Trepanation System.
    M. Engelhardt, P. Bast, N. Jeblink, W. Lauer, A. Popovic, H. Eufinger, M. Scholz, A. Christmann, A. Harders, K. Radermacher, K. Schmieder (2006)
    Minimally Invasive Neurochirurgy, 49, 98-103.
        PDF

  • On a Strategy to Develop Robust and Simple Tariffs from Motor Vehicle Insurance Data.
    Andreas Christmann (2005).
    Acta Mathematicae Applicatae Sinica, English Series, 21, 193-208.


  • Determination of hyper-parameters for kernel based classification and regression..
    Andreas Christmann, Karsten Lübke, Marcos Marin-Galiano, Stefan Rüping (2005).
    University of Dortmund, SFB-475, TR-38/2005.
        PDF

  • On Robustness Properties of Convex Risk Minimization Methods for Pattern Recognition.
    Andreas Christmann, Ingo Steinwart (2004).
    Journal of Machine Learning Research, 5, 1007-1034.
        PDF

  • An approach to model complex high-dimensional insurance data
    Andreas Christmann (2004).
    Allgemeines Statistisches Archiv, 88, 375-397.
        PDF

  • Insurance: an R-Program to Model Insurance Data..
    Andreas Christmann, Marcos Marin Galiano (2004).
    University of Dortmund, SFB-475, Technical Report.
        PDF

  • Robustness against separation and outliers in logistic regression.
    Peter J. Rousseeuw, Andreas Christmann (2003).
    Computational Statistics and Data Analysis, 43, 315-332.
        PDF

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RECENT PRESENTATIONS

  • On Stability Properties of Support Vector Machines.
    Empirical inference symposium in honour of Prof. Dr. V.N. Vapnik's. Max Planck Institute, Tübingen, December 08-10, 2011.
  • On stability and bootstrap of support vector machines.
    Dagstuhl Symposium on "Mathematical and Computational Foundations of Learning Theory". July 17-22, 2011.
  • Estimation of heteroscedasticity with support vector machines.
    International Conference on Robust Statistics (ICORS 2011), Valladolid (Spain), June 27 - July 01, 2011.
  • Fitting Additive Models with Support Vector Machines: Consistency and Robustness.
    3rd International Conference of the ERCIM Working Group on Computing and Statistics (ERCIM'10), London, December 10-12, 2010.
  • Universal Kernels on Non-Standard Input Spaces.
    NIPS 2010, Vancouver, December 06-09, 2010. (Poster).
  • Semiparametric Modelling with Support Vector Machines: Consistency and Robustness.
    International Conference on Robust Statistics, Prague, June 28 - July 2, 2010.
  • Tutorial on Support vector machines.
    Tutorial workshop on Robustness: Basic concepts and applications. Prague, June 26-27, 2010.
  • On Learning and Robustness Properties of Support Vector Machines.
    University of British Columbia, Vancouver, Canada, December 8, 2009.
  • Support Vector Machines.
    Summer School, Ovronnaz, Switzerland, September 8-12, 2009.
  • On Consistency and Robustness of Support Vector Machines.
    ISI-2009, Durban, South Africa, August 16-22, 2009.
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SELECTED FINISHED PROJECTS

  • Construction of effective and fair insurance tariffs
    Cooperation partner: Verband öffentlicher Versicherer, Düsseldorf, Germany.
    Goals: Use methods from statistical machine learning and extreme value theory for the construction of insurance tariffs.

     
  • Risk differentiation in high-dimensional data structures.
    Project B7 in the Sonderforschungsbereich "Reduction of complexity for multivariate data structures" (SFB-475) at the Department of Statistics, University of Dortmund, Germany.
    Goals: Identification and modelling of complex dependency structures in high-dimensional and complex data sets.

     
  • Statistical software and algorithms
    DoMuS, University of Dortmund, Germany.
    Goals: Investigation of statistical properties of modern statistical methods, e.g. support vector machine and kernel logistic regression.

     
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SOFTWARE

  • R programs
    • insurance: an R-Program to Model insurance Data
      (M. Marin-Galiano, A. Christmann)
    • noverlap: n_overlap in binary regression models
    • ncomplete: n_complete in binary regression models
    noverlap, ncomplete, and an R-implementation of the S-PLUS code hlr for hidden logistic regression are available also from the CRAN-Mirrors.

  • S-Plus
    • hbdp: robust estimators with high breakdown points in generalized linear models
    • hlr: estimators MEL and WEMEL in the hidden logistic regression model
    • robust Cronbach's alpha: robust estimators of Cronbach's alpha (S-PLUS and SAS)
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TEACHING

Some Courses

Link to recent courses
  • Einführung in die Stochastik
  • Einführung in die Statistik
  • Support Vector Machines
  • Lineare Modelle
  • Oberseminar
  • Mathematical Statistics (Bachelor program, VUB, Brussels)
  • Generalized Linear Models (Master program, English, VUB and ULB, Brussels)
  • Mathematical Statistics 2 (Master program, English, ULB, Brussels).
  • New Developments in Mathematics (Bachelor program, VUB, Brussels).
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HOW TO REACH ME

  • To see a map of the city Bayreuth, you can click on the next link and type in the word Bayreuth. City map. The university campus is located in the south of Bayreuth.
  • Campus of the university as PDF file My office is in building NW II.
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SHORT CV

    1988 Diploma in Statistics, University of Dortmund, Germany
    1989-1990 Scholarship of the Alfried Krupp von Bohlen und Halbach foundation
    1992 Dr. rer. nat., Department of Statistics, University of Dortmund
    1990-1994 Researcher, Department of Statistics, University of Dortmund
    1994 Statistician, Institut für Medizinisches Marketing GmbH, Hamburg
    1994-2003 Statistician, Statistical Consulting Center, University of Dortmund
    1998 Habilitation, Department of Statistics, University of Dortmund
    2003-2006 Assistant Professor (C2) of Data Analysis, Department of Statistics, University of Dortmund
    10/2004-09/2005 Visiting Professor, Katholieke Universiteit Leuven, Belgium
    04/2005-09/2005 Professor of Biostatistics (W2, Deputy), Department of Statistics, University of Dortmund
    02/2006-01/2008   Professor of Statistics, Department of Mathematics, Vrije Universiteit Brussel, Belgium
    since 02/2008 Chair of Stochastics, Department of Mathematics, University of Bayreuth
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LINKS

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