Convergence of Smoothed Empirical Measures with Applications to Entropy Estimation

Keyphrases

• Empirical Measure 100%
• Divergence 100%
• Kullback-Leibler Divergence 100%
• Entropy Estimation 100%
• Wasserstein Distance 100%
• Plug-in Estimator 100%
• Convergence Rate 66%
• K-nearest Neighbor (K-NN) 66%
• Kernel Density Estimation 66%
• Differential Entropy 66%
• Approximation Results 33%
• Random Variables 33%
• Input-output 33%
• Nonparametric 33%
• Information Flow 33%
• Numerical Results 33%
• Noise Effects 33%
• Mutual Information 33%
• Total Variation 33%
• Total Variation Distance 33%
• Additive White Gaussian Noise Channel 33%
• Approximation Error 33%
• Information Bottleneck 33%
• Identically Distributed 33%
• I(d) 33%
• Rate Change 33%
• Sample Complexity 33%
• Entropy Estimator 33%
• Gaussian Kernel 33%
• Absolute Error 33%
• Deep Neural Network 33%
• Minimax Rate 33%
• Rate-optimal 33%
• Regularizing Effect 33%
• Parametric Rate 33%
• Risk of Error 33%
• Plug-in Approach 33%
• Finite Inputs 33%
• Empirical Approximation 33%
• Statistical Distance 33%

Mathematics

• Kullback-Leibler Divergence 100%
• Wasserstein Distance 100%
• Gaussian Distribution 66%
• Convergence Rate 66%
• Kernel Density Estimation 66%
• Nearest Neighbor 33%
• Random Variable 33%
• Parametric 33%
• Mutual Information 33%
• Total Variation Distance 33%
• Total Variation 33%
• Change Rate 33%
• Approximation Error 33%
• Minimax 33%
• Superiority 33%
• Absolute Error 33%
• Deep Neural Network 33%
• Considered Problem 33%
• Nearest Neighbor Method 33%
• Finite Input 33%

Economics, Econometrics and Finance

• Kullback-Leibler Divergence 100%