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  • Language
    Jupyter Notebook
  • License
    MIT License
  • Created almost 5 years ago
  • Updated over 2 years ago

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Repository Details

Scripts and notebooks to reproduce the experiments and analyses of the paper Adrian Englhardt, Holger Trittenbach, Daniel Kottke, Bernhard Sick, Klemens Böhm, "Efficient SVDD sampling with approximation guarantees for the decision boundary", Machine Learning (2022).