New Upper bounds for KL-divergence Based on Integral Norms
Probability
2024-10-31 v2 Information Theory
math.IT
Abstract
In this paper, some new upper bounds for Kullback-Leibler divergence(KL-divergence) based on and norms of density functions are discussed. Our findings unveil that the convergence in KL-divergence sense sandwiches between the convergence of density functions in terms of and norms. Furthermore, we endeavor to apply our newly derived upper bounds to the analysis of the rate theorem of the entropic conditional central limit theorem.
Cite
@article{arxiv.2409.00934,
title = {New Upper bounds for KL-divergence Based on Integral Norms},
author = {Liuquan Yao and Songhao Liu},
journal= {arXiv preprint arXiv:2409.00934},
year = {2024}
}
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