Alex Dytso

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20242026

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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.ST2025

Generalized Linear Models with 1-Bit Measurements: Asymptotics of the Maximum Likelihood Estimator

Jaimin Shah, Martina Cardone, Cynthia Rush +1

This work establishes regularity conditions for consistency and asymptotic normality of the multiple parameter maximum likelihood estimator(MLE) from censored data, where the censo…

math.ST2024

$L^{1}$ 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

Generalized Linear Models with 1-Bit Measurements: Asymptotics of the Maximum Likelihood Estimator

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