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Dr. Alexander Munteanu

Mathematische Statistik und biometrische Anwendungen

Kontakt

Mathematics Building,
Raum E16b
0231 755 - 7885
0231 755 - 5303
Fakultät Statistik
Technische Universität Dortmund
44221 Dortmund


Research interests

I am mainly interested in the design and analysis of algorithms for tackling the challenges of massive data. This particularly involves several fields of research such as

  • streaming and distributed algorithms,
  • randomized linear algebra,
  • machine learning,
  • computational statistics,
  • computational geometry,
  • convex optimization.
  • I am also interested in cooperating on possible applications.

    Publications

    2019

    • Stefan Meintrup, Alexander Munteanu, Dennis Rohde.
      Random projections and sampling algorithms for clustering of high-dimensional polygonal curves.
      Advances in Neural Information Processing Systems (NeurIPS), 2019 (to appear).
       
    • Alexander Munteanu, Amin Nayebi, Matthias Poloczek.
      A framework for Bayesian optimization in embedded subspaces.
      International Conference on Machine Learning (ICML), 2019.
       
    • Amer Krivosija, Alexander Munteanu.
      Probabilistic smallest enclosing ball in high dimensions via subgradient sampling.
      Symposium on Computational Geometry (SoCG), 2019.
      European Workshop on Computational Geometry (EuroCG), 2019.
       

    2018

    • Alexander Munteanu, Chris Schwiegelshohn, Christian Sohler, David Woodruff.
      On coresets for logistic regression.
      Advances in Neural Information Processing Systems (NeurIPS), 2018.
       
    • Alexander Munteanu.
      On large-scale probabilistic and statistical data analysis.
      PhD Thesis. Technische Universität Dortmund, 2018.
       
    • Kristian Kersting, Alejandro Molina, Alexander Munteanu.
      Core dependency networks.
      AAAI Conference on Artificial Intelligence (AAAI), 2018.
       
    • Alexander Munteanu, Chris Schwiegelshohn.
      Coresets - methods and history: a theoreticians design pattern for approximation and streaming algorithms.
      KI special issue on "Algorithmic Challenges and Opportunities of Big Data", 32(1):37-53, 2018.
       

    2017

    • Leo N. Geppert, Katja Ickstadt, Alexander Munteanu, Jens Quedenfeld, Christian Sohler.
      Random projections for Bayesian regression.
      Statistics and Computing, 27(1):79-101, 2017.
       

    2016

    • Alexander Munteanu, Max Wornowizki.
      Correcting statistical models via empirical distribution functions.
      Computational Statistics, 31(2):465-495, 2016.
       

    2014

    • Dan Feldman, Alexander Munteanu, Christian Sohler.
      Smallest enclosing ball for probabilistic data.
      Symposium on Computational Geometry (SoCG), 2014.
       
    • Marc Heinrich, Alexander Munteanu, Christian Sohler.
      Asymptotically exact streaming algorithms.
      ArXiv preprint, CoRR abs/1408.1847, 2014.
       

    Teaching

    • Winter 19/20: Seminar "Foundations of Data Science" & Colloquium of the Dortmund Data Science Center
    • Summer 19: Colloquium of the Dortmund Data Science Center
    • Winter 18/19: Substitute for the seminar "Algorithmen zur präferenzbasierten Entscheidungsfindung"