Federico Camerlenghi | DeepAI

AI Chat

Featured Co-authors

David B. Dunson
94 publications
Tamara Broderick
53 publications
Stefano Favaro
40 publications
Barbara E. Engelhardt
28 publications
Antonietta Mira
27 publications
Fadhel Ayed
16 publications
Mario Beraha
15 publications
Abel Rodriguez
15 publications
Alessandra Guglielmi
13 publications
Zacharie Naulet
12 publications
Raffaele Argiento
11 publications

∙ 02/17/2023

Normalized Random Meaures with Interacting Atoms for Bayesian Nonparametric Mixtures

The study of almost surely discrete random probability measures is an ac...

0 Mario Beraha, et al. ∙

∙ 03/14/2022

A Bayesian Nonparametric Approach to Species Sampling Problems with Ordering

Species-sampling problems (SSPs) refer to a vast class of statistical pr...

0 Cecilia Balocchi, et al. ∙

∙ 01/28/2022

Wasserstein posterior contraction rates in non-dominated Bayesian nonparametric models

Posterior contractions rates (PCRs) strengthen the notion of Bayesian co...

0 Federico Camerlenghi, et al. ∙

∙ 11/03/2021

On Johnson's "sufficientness" postulates for features-sampling models

In the 1920's, the English philosopher W.E. Johnson introduced a charact...

0 Federico Camerlenghi, et al. ∙

∙ 08/26/2021

Contaminated Gibbs-type priors

Gibbs-type priors are widely used as key components in several Bayesian ...

0 Federico Camerlenghi, et al. ∙

∙ 06/29/2021

Scaled process priors for Bayesian nonparametric estimation of the unseen genetic variation

There is a growing interest in the estimation of the number of unseen fe...

0 Federico Camerlenghi, et al. ∙

∙ 09/23/2020

An Information Theoretic approach to Post Randomization Methods under Differential Privacy

Post Randomization Methods (PRAM) are among the most popular disclosure ...

0 Fadhel Ayed, et al. ∙

∙ 08/17/2020

A Common Atom Model for the Bayesian Nonparametric Analysis of Nested Data

The use of high-dimensional data for targeted therapeutic interventions ...

0 Francesco Denti, et al. ∙

∙ 12/11/2019

More for less: Predicting and maximizing genetic variant discovery via Bayesian nonparametrics

While the cost of sequencing genomes has decreased dramatically in recen...

0 Lorenzo Masoero, et al. ∙

∙ 10/11/2019

Nonparametric Bayesian multi-armed bandits for single cell experiment design

The problem of maximizing cell type discovery under budget constraints i...

0 Federico Camerlenghi, et al. ∙

∙ 02/27/2019

Consistent estimation of the missing mass for feature models

Feature models are popular in machine learning and they have been recent...

0 Fadhel Ayed, et al. ∙

∙ 02/27/2019

A Good-Turing estimator for feature allocation models

Feature allocation models generalize species sampling models by allowing...

0 Fadhel Ayed, et al. ∙

∙ 02/14/2019

Optimal disclosure risk assessment

Protection against disclosure is a legal and ethical obligation for agen...

0 Federico Camerlenghi, et al. ∙

∙ 06/25/2018

On consistent estimation of the missing mass

Given n samples from a population of individuals belonging to different ...

0 Fadhel Ayed, et al. ∙

∙ 01/15/2018

Latent nested nonparametric priors

Discrete random structures are important tools in Bayesian nonparametric...

0 Federico Camerlenghi, et al. ∙

Are you a researcher?
Expose your work
to one of the largest
A.I. communities in the world