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An Information Theoretic approach to Post Randomization Methods under Differential Privacy
Post Randomization Methods (PRAM) are among the most popular disclosure ...
09/23/2020 ∙ by Fadhel Ayed, et al. ∙
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A Common Atom Model for the Bayesian Nonparametric Analysis of Nested Data
The use of high-dimensional data for targeted therapeutic interventions ...
08/17/2020 ∙ by Francesco Denti, et al. ∙
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More for less: Predicting and maximizing genetic variant discovery via Bayesian nonparametrics
While the cost of sequencing genomes has decreased dramatically in recen...
12/11/2019 ∙ by Lorenzo Masoero, et al. ∙
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Nonparametric Bayesian multi-armed bandits for single cell experiment design
The problem of maximizing cell type discovery under budget constraints i...
10/11/2019 ∙ by Federico Camerlenghi, et al. ∙
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Consistent estimation of the missing mass for feature models
Feature models are popular in machine learning and they have been recent...
02/27/2019 ∙ by Fadhel Ayed, et al. ∙
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A Good-Turing estimator for feature allocation models
Feature allocation models generalize species sampling models by allowing...
02/27/2019 ∙ by Fadhel Ayed, et al. ∙
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Optimal disclosure risk assessment
Protection against disclosure is a legal and ethical obligation for agen...
02/14/2019 ∙ by Federico Camerlenghi, et al. ∙
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On consistent estimation of the missing mass
Given n samples from a population of individuals belonging to different ...
06/25/2018 ∙ by Fadhel Ayed, et al. ∙
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Latent nested nonparametric priors
Discrete random structures are important tools in Bayesian nonparametric...
01/15/2018 ∙ by Federico Camerlenghi, et al. ∙
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