Hasso-Plattner-Institut
Prof. Dr. Tobias Friedrich
  
 

Karen Seidel

Research Group Algorithm Engineering
Hasso Plattner Institute
Prof.-Dr.-Helmert-Str. 2-3
D-14482 Potsdam

Office: A-1.3
Tel.: +49 331 5509-410
E-Mail: Karen.Seidel(at)hpi.de

Research Interests

I am interested in machine and human learning of mathematics and computer science.

My current main research interest lies in algorithmic learning theory with its connections to artificial intelligence, cognitive science and various areas of computer science. I aim at giving an intuition about how memory restrictions and desired properties of the learner's behavior (while learning) effect what is learnable. For this I provide and employ insights from computability theory and descriptive set theory.

Publications

[ 2018 ] [ 2017 ] [ 2013 ]

2018 [ to top ]

  • InformantLearning.pdf
    Aschenbach, Martin; Kötzing, Timo; Seidel, Karen Learning from Informants: Relations between Learning Success Criteria. ArXiv 2018: 37
     
  • Graph_Homomorphisms_MFCS.pdf
    Göbel, Andreas; Lagodzinski, J. A. Gregor; Seidel, Karen Counting Homomorphisms to Trees Modulo a Prime. International Symposium on Mathematical Foundations of Computer Science (MFCS) 2018: 49:1-49:13
     
  • 1802.06103.pdf
    Göbel, Andreas; Lagodzinski, J. A. Gregor; Seidel, Karen Counting Homomorphisms to Trees Modulo a Prime. arXiv 2018
     

2017 [ to top ]

  • BzMU-2017-SEIDEL.pdf
    Seidel, Karen Zu mathematischen Argumentationen eines Experten aus einer semiotischen Perspektive. Beiträge zum Mathematikunterricht 2017 2017: 897-900
     
  • KoetzingSchirneckSeidel-2017-NormalFormsInSemanticLanguageLearning.pdf
    Kötzing, Timo; Schirneck, Martin; Seidel, Karen Normal Forms in Semantic Language Identification. International Conference on Algorithmic Learning Theory (ALT) 2017: 493-516
     
  • AutomaticLearningFromRepetitiveText.pdf
    Hölzl, Rupert; Jain, Sanjay; Schlicht, Philipp; Seidel, Karen; Stephan, Frank Automatic Learning from Repetitive Texts. International Conference on Algorithmic Learning Theory (ALT) 2017: 129-150
     

2013 [ to top ]

  • KoepkeSchlichtSeidel-2013-AMinimalPrikryTypeForcingForSingularizingAMeasurableCardinal.pdf
    Koepke, Peter; Räsch, Karen; Schlicht, Philipp A minimal Prikry-type forcing for singularizing a measurable cardinal. The Journal of Symbolic Logic 2013: 85-100
     

Selected Conferences, Workshops and Seminars

10/2017 International Conference on Algorithmic Learning Theory
09/2017 Herbsttagung des GDM-Arbeitskreises Mathematik und Bildung
08/2017 Arbeitstreff en Computability and Reducibility
02/2017 Jahrestagung der Gesellschaft für Didaktik der Mathematik
07/2016 International Congress on Mathematics Education
02/2011 Winter School in Abstract Analysis Section Set Theory
01/2010 Indian School on Logic and its Applications