14 papers
Sub-Gaussian Concentration and Entropic Normality of the Maximum Likelihood Estimator
Leighton P. Barnes, Alex Dytso
It is well known that, under standard regularity conditions, the maximum likelihood estimator (MLE) satisfies a central limit theorem and converges in distribution to a Gaussian ra…
The Binomial Channel: On Capacity, Optimal Inputs, and Beta-Binomial Approximation
Antonino Favano, Mohammadamin Baniasadi, Ian Zieder +2
We study the binomial channel with input alphabet and output alphabet . We investigate its capacity and the structure of the capacity-achieving input and outp…
Functional uniqueness and stability of Gaussian priors in optimal L1 estimation
Leighton Barnes, Alex Dytso
We study when optimal Bayesian estimators under Gaussian noise are approximately linear, and what this implies about the underlying prior distribution. Consider the classical model…
An Improved Lower Bound on Support Size of Capacity-Achieving Inputs for the Binomial Channel: Extended version
Mohammadamin Baniasadi, Luca Barletta, Alex Dytso
We study the binomial channel and the structure of its capacity-achieving input and output distributions. It is known that the capacity-achieving input distribution is discrete and…
Support Size of -Capacity-Achieving Inputs for the Amplitude-Constrained AWGN Channel
Luca Barletta, Alex Dytso
We study the amplitude-constrained additive white Gaussian noise (AWGN) channel from the perspective of near-optimal input distributions. While it is known that the capacity-achiev…
-Mutual Information for the Gaussian Noise Channel
Mohammad Milanian, Alex Dytso, Martina Cardone
In this paper, we study Sibson's -mutual information in the context of the additive Gaussian noise channel. While the classical case is well understood and admits deep co…