rezaqorbani / f-CMI

Information-theoretic generalization bounds for black-box algorithms

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Replicating the experiments

  1. Open .bashrc or .zshrc (depending which shell you use) and add a line “export $DATA_DIR={path-of-the-data-dir}.
  2. Generate the commands for the experiment using scripts/fcmi_scripts.py script.
  3. Parse the result of the experiment using the scripts/fcmi_parse_results.py script.
  4. Use the notebooks/fcmi-plots.ipynb to generate plots from the parsed results.

Requirements

  • Basic libraries such as numpy, scipy, tqdm, matplotlib, and seaborn.
  • We used Pytorch 1.7.0, but higher versions should work too.

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Information-theoretic generalization bounds for black-box algorithms

License:MIT License


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Language:Python 98.5%Language:Jupyter Notebook 1.5%