Saarland University, Machine Learning Group, Fak. MI - Mathematik und Informatik, Campus E1 1, 66123 Saarbrücken, Germany     

Machine Learning Group
Department of Mathematics and Computer Science - Saarland University

THOMAS BÜHLER

Researcher/Ph.D. Student,
Faculty of Mathematics and Computer Science,
Saarland University

Address:
Building E 1 1, Room 227
Universität des Saarlandes
Postfach 15 11 50
D - 66041 Saarbrücken
Germany

phone: +49 (0) 681 302 57332

 

ABOUT ME

Since April 2009 I am a researcher and Ph.D. student in the Machine Learning Group at Saarland University, under supervision of Prof. Matthias Hein. I obtained B.Sc. and M.Sc. degrees in Computer Science from Saarland University in 2007 and 2009, respectively.

RESEARCH

My general research interests are in machine learning and optimization, as well as applications in network analysis, information retrieval and computer vision.

The main focus during my PhD was on tight relaxations of combinatorial problems, their connection to nonlinear eigenproblems as well as their algorithmical solution. This lead to several applications in unsupervised learning in a graph-based setting which were demonstrated to have a superior performance compared to methods based on standard spectral relaxations.

SOFTWARE

TALKS ON THE WEB

  • Constrained fractional set programs and their application in local clustering and community detection
    ICML 2013, Atlanta, GA, USA
    View on techtalks.tv
  • Spectral Clustering based on the graph p-Laplacian
    ICML 2009, Montreal, Canada
    View on videolectures.net

PUBLICATIONS

  • S. Rangapuram, T. Bühler and M. Hein
    Towards Realistic Team Formation in Social Networks based on Densest Subgraphs
    In Proc. 22nd International World Wide Web Conference (WWW 2013), 1077-1088, 2013 PDF . Code.
  • T. Bühler, S. Rangapuram, S. Setzer and M. Hein
    Constrained fractional set programs and their application in local clustering and community detection
    In Proc. 30th International Conference on Machine Learning (ICML 2013), JMLR W&CP 28 (1): 624-632, 2013 PDF  (Supplementary material: PDF ).
  • M. Hein and T. Bühler
    An inverse power method for nonlinear eigenproblems with applications in 1-spectral clustering and sparse PCA
    In Advances in Neural Information Processing Systems 23 (NIPS 2010), 847-855, 2010. PDF  (Supplementary material: PDF ). Code.
  • T. Bühler and M. Hein
    Spectral Clustering based on the graph p-Laplacian
    In Proc. 26th International Conference on Machine Learning (ICML 2009), 81-88, Omnipress, 2009. PDF  (Supplementary material: PDF  - Errata of Supp. Mat.: PDF ). Code.
  • N. Slesareva, T. Bühler, K. Hagenburg, J. Weickert, A. Bruhn, Z. Karni and H.-P. Seidel
    Robust Variational Reconstruction from Multiple Views
    In Proc. 15th Scandinavian Conference on Image Analysis (SCIA 2007), 173-182, Springer, 2007. PDF 

 



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