5 papers
Non-asymptotic approximations of Gaussian neural networks via second-order Poincaré inequalities
Alberto Bordino, Stefano Favaro, Sandra Fortini
There is a recent and growing literature on large-width asymptotic and non-asymptotic properties of deep Gaussian neural networks (NNs), namely NNs with weights initialized as Gaus…
Optimal estimation of high-order missing masses, and the rare-type match problem
Stefano Favaro, Zacharie Naulet
Consider a random sample from an unknown discrete distribution on a countable alphabet , and let $(Y_{n,j})_{j\g…
Random measure priors in Bayesian recovery from sketches
Mario Beraha, Stefano Favaro, Matteo Sesia
This paper introduces a Bayesian nonparametric approach to frequency recovery from lossy-compressed discrete data, leveraging all information contained in a sketch obtained through…
Bayesian Nonparametric Inference for "Species-sampling" Problems
Cecilia Balocchi, Stefano Favaro, Zacharie Naulet
Given an observed sample from a population of individuals belonging to species, "species-sampling" problems (SSPs) call for estimating some features of the unknown species composit…
A Bayesian Nonparametric Approach to Species Sampling Problems with Ordering
Cecilia Balocchi, Federico Camerlenghi, Stefano Favaro
Species-sampling problems (SSPs) refer to a vast class of statistical problems calling for the estimation of (discrete) functionals of the unknown species composition of an unobser…