Evidential reasoning (ER) rule has been widely used in dealing with uncertainty. As an
important parameter to measure the inherent property of evidence, the evidence reliability …

The Shannon lower bound has been the subject of several important contributions by
Berger. This paper surveys Shannon bounds on rate-distortion problems under mean …

We study the problem of choosing the copula when the marginal distributions of a random
vector are not all continuous. Inspired by four motivating examples including simulation from …

We establish the fundamental limits of lossless analog compression by considering the
recovery of arbitrary random vectors x∈ R m from the noiseless linear measurements y= Ax …

Abstract We introduce Minimal Achievable Sufficient Statistic (MASS) Learning, a machine
learning training objective for which the minima are minimal sufficient statistics with respect …

Artifical Neural-Network-based (ANN-based) lossy compressors have recently obtained
striking results on several sources. Their success may be ascribed to an ability to identify the …

We consider the differential entropy of probability measures absolutely continuous with
respect to a given σ σ-finite “reference” measure on an arbitrary measure space. We state …

In this paper, we provide three applications for-divergences:(i) we introduce Sanov's upper
bound on the tail probability of the sum of independent random variables based on super …

This paper is concerned with the lossy compression of general random variables,
specifically with rate-distortion theory and quantization of random variables taking values in …

This paper is concerned with a rate-distortion theory for sequences of iid random variables
with general distribution supported on general sets including manifolds and fractal sets …