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Towards Generalization beyond Pointwise Learning: A Unified Information-theoretic Perspective

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Towards Generalization beyond Pointwise Learning: A Unified Information-theoretic Perspective (ICML 2024)

Replicating the experiments

  1. Generate the commands for the desired experiment using the scripts/fcmi_scripts.py script.
  2. Parse the result of the experiment using the scripts/fcmi_parse_results.py script.
  3. Use the scripts/pairwise_plots.py 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.

Cite

@inproceedings{
    dong2024towards,
    title={Towards Generalization beyond Pointwise Learning: A Unified Information-theoretic Perspective},
    author={Yuxin Dong and Tieliang Gong and Hong Chen and Mengxiang Li and Zhongjiang He and Shuangyong Song and Chen Li},
    booktitle={International Conference on Machine Learning},
    year={2024},
    organization={PMLR}
}

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