3 papers
math.ST2026
Differentially Private Inference for Longitudinal Linear Regression
Getoar Sopa, Marco Avella Medina, Cynthia Rush
Differential Privacy (DP) provides a rigorous framework for releasing statistics while protecting individual information present in a dataset. Although substantial progress has bee…
math.ST2026
Statistical Guarantees for Data-driven Posterior Tempering
Ruchira Ray, Marco Avella Medina, Cynthia Rush
Posterior tempering reduces the influence of the likelihood in the calculation of the posterior by raising the likelihood to a fractional power . The resulting power posterior…
math.ST2025
A theoretical framework for M-posteriors: frequentist guarantees and robustness properties
Juraj Marusic, Marco Avella Medina, Cynthia Rush
We provide a theoretical framework for a wide class of generalized posteriors that can be viewed as the natural Bayesian posterior counterpart of the class of M-estimators in the f…