2 citations · 5 across the 7 of their papers we have counts for
12 papers
Wasserstein posterior contraction rates in non-dominated Bayesian nonparametric models
Federico Camerlenghi, Emanuele Dolera, Stefano Favaro +1
Posterior contractions rates (PCRs) strengthen the notion of Bayesian consistency, quantifying the speed at which the posterior distribution concentrates on arbitrarily small neigh…
On Johnson's "sufficientness" postulates for features-sampling models
Federico Camerlenghi, Stefano Favaro
In the 1920's, the English philosopher W.E. Johnson introduced a characterization of the symmetric Dirichlet prior distribution in terms of its predictive distribution. This is typ…
Contaminated Gibbs-type priors
Federico Camerlenghi, Riccardo Corradin, Andrea Ongaro
Gibbs-type priors are widely used as key components in several Bayesian nonparametric models. By virtue of their flexibility and mathematical tractability, they turn out to be pred…
An Information Theoretic approach to Post Randomization Methods under Differential Privacy
Fadhel Ayed, Marco Battiston, Federico Camerlenghi
Post Randomization Methods (PRAM) are among the most popular disclosure limitation techniques for both categorical and continuous data. In the categorical case, given a stochastic…
A Common Atom Model for the Bayesian Nonparametric Analysis of Nested Data
Francesco Denti, Federico Camerlenghi, Michele Guindani +1
The use of high-dimensional data for targeted therapeutic interventions requires new ways to characterize the heterogeneity observed across subgroups of a specific population. In p…
More for less: Predicting and maximizing genetic variant discovery via Bayesian nonparametrics
Lorenzo Masoero, Federico Camerlenghi, Stefano Favaro +1
While the cost of sequencing genomes has decreased dramatically in recent years, this expense often remains non-trivial. Under a fixed budget, then, scientists face a natural trade…