  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 ).
