Conditional mutual information bounds ideal prediction errors for feature subsets and supplies a stopping condition for greedy selection algorithms.
Estimation of entropy and mutual information,
2 Pith papers cite this work. Polarity classification is still indexing.
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Uses Chow parameters of Boolean threshold functions to estimate Rényi entropies of n-delay PUFs up to n=10, finding Shannon entropy asymptotically quadratic in n and close to max-entropy.
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Feature Selection via Mutual Information: New Theoretical Insights
Conditional mutual information bounds ideal prediction errors for feature subsets and supplies a stopping condition for greedy selection algorithms.
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Entropy Estimation of Physically Unclonable Functions via Chow Parameters
Uses Chow parameters of Boolean threshold functions to estimate Rényi entropies of n-delay PUFs up to n=10, finding Shannon entropy asymptotically quadratic in n and close to max-entropy.