17 citations · 27 across the 14 of their papers we have counts for
5 papers · 1 filter
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…
Nonparametric Bayesian multi-armed bandits for single cell experiment design
Federico Camerlenghi, Bianca Dumitrascu, Federico Ferrari +2
The problem of maximizing cell type discovery under budget constraints is a fundamental challenge for the collection and analysis of single-cell RNA-sequencing (scRNA-seq) data. In…
Consistent estimation of the missing mass for feature models
Fadhel Ayed, Marco Battiston, Federico Camerlenghi +1
Feature models are popular in machine learning and they have been recently used to solve many unsupervised learning problems. In these models every observation is endowed with a fi…
Optimal disclosure risk assessment
Federico Camerlenghi, Stefano Favaro, Zacharie Naulet +1
Protection against disclosure is a legal and ethical obligation for agencies releasing microdata files for public use. Consider a microdata sample of size from a finite populat…
A Good-Turing estimator for feature allocation models
Fadhel Ayed, Marco Battiston, Federico Camerlenghi +1
Feature allocation models generalize species sampling models by allowing every observation to belong to more than one species, now called features. Under the popular Bernoulli prod…