Papers › Formal Limitations on the Measurement of Mutual Information
Formal Limitations on the Measurement of Mutual Information
David McAllester, Karl Stratos
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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