H. V. Poor

activity

20182025

most citedMMSE Bounds Under Kullback-Leibler Divergence Constraints on the Joint Input-Output Distribution

1 citations · 2 across the 5 of their papers we have counts for

collaborators

Showing math.STShow all

3 papers · 1 filter

math.ST2025

Linearity-Inducing Priors for Poisson Parameter Estimation Under $L^{1}$ Loss

Leighton P. Barnes, Alex Dytso, H. Vincent Poor

We study prior distributions for Poisson parameter estimation under $L^{1}$ loss. Specifically, we construct a new family of prior distributions whose optimal Bayesian estimators (th…

math.ST2024★ 1 cited

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 $X$ from noisy observations $Y = X + Z$ , where $Z$ is a standard normal vector, under the $L^{p}$ fidelity criterion. This work establ…

math.ST2023

$L^{1}$ Estimation: On the Optimality of Linear Estimators

Leighton P. Barnes, Alex Dytso, Jingbo Liu +1

Consider the problem of estimating a random variable $X$ from noisy observations $Y = X + Z$ , where $Z$ is standard normal, under the $L^{1}$ fidelity criterion. It is well known that…

Linearity-Inducing Priors for Poisson Parameter Estimation Under L1 Loss

Multivariate Priors and the Linearity of Optimal Bayesian Estimators under Gaussian Noise

L1 Estimation: On the Optimality of Linear Estimators

Linearity-Inducing Priors for Poisson Parameter Estimation Under $L^{1}$ Loss

$L^{1}$ Estimation: On the Optimality of Linear Estimators