Breaking the Bandwidth Barrier: Geometrical Adaptive Entropy Estimation

NeurIPS 2016 Weihao GaoSewoong OhPramod Viswanath

Estimators of information theoretic measures such as entropy and mutual information are a basic workhorse for many downstream applications in modern data science. State of the art approaches have been either geometric (nearest neighbor (NN) based) or kernel based (with a globally chosen bandwidth)... (read more)

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