3 papers
stat.ME2026
Adaptive Bayesian Structure Learning of DAGs With Non-conjugate Prior
S. Nazari, M. Arashi, A. Sadeghkhani
Directed Acyclic Graphs (DAGs) are solid structures used to describe and infer the dependencies among variables in multivariate scenarios. Having a thorough comprehension of the ac…
stat.ME2026
Robust high-dimensional Bayesian regression with non-Gaussian errors under global--local shrinkage priors
Mohammad Arashi
Multivariate regression with many correlated responses and predictors commonly violates Gaussian error assumptions due to heavy tails, outliers, and asymmetry. Gaussian procedures…
cs.LG2026
Stein-Rule Shrinkage for Stochastic Gradient Estimation in High Dimensions
M. Arashi, M. Amintoosi
Stochastic gradient methods are central to large-scale learning, but they treat mini-batch gradients as unbiased estimators, which classical decision theory shows are inadmissible…