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Dr. Alexander Munteanu


Address: Technische Universität Dortmund
Fakultät für Informatik, Lehrstuhl 2
D-44221 Dortmund
Germany
Office: Campus Nord, Otto-Hahn-Straße 14, Room 312
E-mail: alexander.munteanutu-dortmund.de
Phone: +49 (0)231 755-2049
Fax: +49 (0)231 755-2047
Alexander


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

Conference Articles

  • Alexander Munteanu, Chris Schwiegelshohn, Christian Sohler, David Woodruff.
    On coresets for logistic regression.
    Advances in Neural Information Processing Systems (NIPS), to appear, 2018.
     

  • Alejandro Molina, Alexander Munteanu, Kristian Kersting.
    Core dependency networks.
    32nd AAAI Conference on Artificial Intelligence (AAAI), 2018.
     

  • Dan Feldman, Alexander Munteanu, Christian Sohler.
    Smallest enclosing ball for probabilistic data.
    30th Annual Symposium on Computational Geometry (SoCG), 2014.
     

Journal Articles

  • 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.
     

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

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

Technical Reports

  • Marc Heinrich, Alexander Munteanu, Christian Sohler.
    Asymptotically exact streaming algorithms.
    ArXiv preprint, CoRR abs/1408.1847, 2014.
     

Theses

Teaching

Supervised research internships

  • Marc Heinrich, École Normale Supérieure, Paris, France (2014)
    Asymptotically exact streaming algorithms

  • Siargey Kachanovich, École Normale Supérieure de Rennes, Rennes, France (2014)
    Ressource-restricted non-parametric regression under structural constraints

Supervised theses

  • Maximilian Freese (2017): Sketch-basierte Bayes-Regression mit MapReduce,
    Bachelor Thesis, TU Dortmund.

  • Niels Lategahn (2016): Vergleich von Methoden zur Auswahl von Beobachtungen bei Regression mit fehlenden Y-Werten,
    Master Thesis, Faculty of Statistics, TU Dortmund.

  • Steffen Müller (2016): Untersuchung von Regression auf eingebetteten Datensätzen unter Verwendung von verschiedenen Abstandsnormen und Penalisierungstermen,
    Master Thesis, Faculty of Statistics, TU Dortmund.

  • Christian Bohr (2015): Sublineare Approximation von Eigenschaften geometrischer Punktmengen mittels Bereichsanfragen,
    Bachelor Thesis, TU Dortmund.

  • Jonathan Rathjens (2015): Hierarchische Bayes-Regression bei Einbettung großer Datensätze,
    Master Thesis, Faculty of Statistics, TU Dortmund.

  • Tobias Heinlein (2013): Algorithms for the j-subspace problem using MapReduce,
    Bachelor Thesis, TU Dortmund.

  • Michael Bulinski (2012): Parallelisierung von Clusteringalgorithmen,
    Bachelor Thesis, TU Dortmund.

  • Ralf Kellermann (2012): Optimierung der Sensorplatzierung für triangulationsbasierte Lokalisierungsverfahren,
    Diploma Thesis, IRF, TU Dortmund.

Review and grading

  • Matthias Buttkus (2017): Über die Ausdrucksstärke eingeschränkter DNNFs,
    Master Thesis, TU Dortmund.

Teaching assistance

  • Summer term 2011: Tutorials for the lecture "Datenstrukturen, Algorithmen und Programmierung 2"

  • Winter term 2010/2011: Tutorials for the lecture "Rechnerstrukturen"