activity
20242026
most citedScale adaptive and robust intrinsic dimension estimation via optimal neighbourhood identification

1 citations · 1 across the 4 of their papers we have counts for

collaborators

10 papers

math.ST2026

Deconvolution in unlinked linear models

Fadoua Balabdaoui, Antonio Di Noia, Cécile Durot

Unlinked regression, in which covariates and responses are observed separately without known correspondence, has recently gained increasing attention. Deconvolution, on the other h…

stat.ML20261 cited

Scale adaptive and robust intrinsic dimension estimation via optimal neighbourhood identification

Antonio Di Noia, Iuri Macocco, Aldo Glielmo +2

The Intrinsic Dimension (ID) is a key concept in unsupervised learning and feature selection, as it is a lower bound to the number of variables which are necessary to describe a sy…

stat.ML2026

A general framework for adaptive nonparametric dimensionality reduction

Antonio Di Noia, Federico Ravenda, Antonietta Mira

Dimensionality reduction is a fundamental task in modern data science. Several projection methods specifically tailored to take into account the non-linearity of the data via local…

math.ST2025

Asymptotic theory for nonparametric testing of -monotonicity in discrete distributions

Fadoua Balabdaoui, Antonio Di Noia

In shape-constrained nonparametric inference, it is often necessary to perform preliminary tests to verify whether a probability mass function (p.m.f.) satisfies qualitative constr…

math.ST2025

Likelihood distortion and Bayesian local robustness

Antonio Di Noia, Fabrizio Ruggeri, Antonietta Mira

Robust Bayesian analysis has been mainly devoted to detecting and measuring robustness w.r.t. the prior distribution. Many contributions in the literature aim to define suitable cl…

math.ST2025

Estimation and goodness-of-fit testing for non-negative random variables with explicit Laplace transform

Lucio Barabesi, Antonio Di Noia, Marzia Marcheselli +2

Many flexible families of positive random variables exhibit non-closed forms of the density and distribution functions and this feature is considered unappealing for modelling purp…