35 citations · 38 across the 8 of their papers we have counts for
8 papers
Linearity-Inducing Priors for Poisson Parameter Estimation Under Loss
Leighton P. Barnes, Alex Dytso, H. Vincent Poor
We study prior distributions for Poisson parameter estimation under loss. Specifically, we construct a new family of prior distributions whose optimal Bayesian estimators (th…
Multivariate Priors and the Linearity of Optimal Bayesian Estimators under Gaussian Noise
Leighton P. Barnes, Alex Dytso, Jingbo Liu +1
Consider the task of estimating a random vector from noisy observations , where is a standard normal vector, under the fidelity criterion. This work establ…
PAC Learnability for Reliable Communication over Discrete Memoryless Channels
Jiakun Liu, Wenyi Zhang, H. Vincent Poor
In practical communication systems, knowledge of channel models is often absent, and consequently, transceivers need be designed based on empirical data. In this work, we study dat…
Estimation: On the Optimality of Linear Estimators
Leighton P. Barnes, Alex Dytso, Jingbo Liu +1
Consider the problem of estimating a random variable from noisy observations , where is standard normal, under the fidelity criterion. It is well known that…
A General Derivative Identity for the Conditional Mean Estimator in Gaussian Noise and Some Applications
Alex Dytso, H. Vincent Poor, Shlomo Shamai
Consider a channel where is an -dimensional random vector, and is a Gaussian vector with a covariance matrix ${\bf \mathsf{K}}_{\b…
MMSE Bounds Under Kullback-Leibler Divergence Constraints on the Joint Input-Output Distribution
Michael Fauß, Alex Dysto, H. Vincent Poor
This paper proposes a new family of lower and upper bounds on the minimum mean squared error (MMSE). The key idea is to minimize/maximize the MMSE subject to the constraint that th…
On the Capacity of the Peak Power Constrained Vector Gaussian Channel: An Estimation Theoretic Perspective
Alex Dytso, Mert Al, H. Vincent Poor +1
This paper studies the capacity of an -dimensional vector Gaussian noise channel subject to the constraint that an input must lie in the ball of radius centered at the origi…
MVG Mechanism: Differential Privacy under Matrix-Valued Query
Thee Chanyaswad, Alex Dytso, H. Vincent Poor +1
Differential privacy mechanism design has traditionally been tailored for a scalar-valued query function. Although many mechanisms such as the Laplace and Gaussian mechanisms can b…