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  title = 	 {Formal Limitations on the Measurement of Mutual Information},
  author =       {McAllester, David and Stratos, Karl},
  booktitle = 	 {Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics},
  pages = 	 {875--884},
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  pdf = 	 {http://proceedings.mlr.press/v108/mcallester20a/mcallester20a.pdf},
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  abstract = 	 {Measuring mutual information from finite data is difficult. Recent work has considered variational methods maximizing a lower bound. In this paper, we prove that serious statistical limitations are inherent to any method of measuring mutual information. More specifically, we show that any distribution-free high-confidence lower bound on mutual information estimated from N samples cannot be larger than O(ln N).}
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