We offer...
Dekobild im Seitenkopf ISMLL
 
People: Prof. Dr. Tom Hanika
Office hour:
C203 Spl, n. V.
Phone, Fax, Email:
Phone:+495121 / 883-40360
Fax:+4905121 / 883-40361
e-mail:
Postal address:
Information Systems and Machine Learning Lab
Universitätsplatz 1
University of Hildesheim
31141 Hildesheim
Germany
Visitor address:
Information Systems and Machine Learning Lab
Samelsonplatz 1
University of Hildesheim
31141 Hildesheim
Germany

Publikationen:

  • Tobias Hille, Maximilian Stubbemann, Tom Hanika (2024):
    Reproducibility and Geometric Intrinsic Dimensionality: An Investigation on Graph Neural Network Research, in arxiv:2403.08438. PDF
  • Maximilian Stubbemann, Tobias Hille, Tom Hanika (2023):
    Selecting Features by their Resilience to the Curse of Dimensionality, in arXiv:2304.02455. PDF
  • Maximilian Stubbemann, Tom Hanika, Friedirch Martin Schneider (2023):
    Intrinsic Dimension for Large-Scale Geometric Learning, in Transactions on Machine Learning Research. PDF
  • Dominik Duerrschnabel, Maximilian Stubbemann, Tom Hanika (2022):
    FCA2VEC: Embedding Techniques for Formal Concept Analysis, in Complex Data Analytics with Formal Concept Analysis. PDF
  • Tobias Koopmann, Maximilian Stubbemann, Matthias Kapa, Michael Paris, Guido Buenstorf, Tom Hanika, Andreas Hotho, Robert Jaeschke, Gerd Stumme (2021):
    Proximity Dimensions and the Emergence of Collaboration: A HypTrails Study on German AI Research, in Scientometrics. PDF
  • Maximilian Stubbemann, Tom Hanika, Gerd Stumme (2022):
    Orometric Methods in Bounded Metric Data, in Advances in Intelligent Data Analysis XVIII. PDF