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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
Pages
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Posts
Looking for a RA
Published:
I was recently awarded a LSE Research and Impact Support Fund (my first grant, hurray, thanks LSE!) and I am now looking for a research assistant to work with me and the UN World Food Programme on predicting food insecurities. Read more
This should have happened some time ago
Published:
I have been fantasising about having a blog for a long time (ok, well, one year at least). Read more
portfolio
Equality, diversity and inclusion
Since 2020, I started working on ED&I topics. Read more
publications
Optimal disclosure risk assessment Permalink
Published in Annals of Statistics, 2021
Federico Camerlenghi, Stefano Favaro, Zacharie Naulet, Francesca Panero
We propose a nonparametric estimator of disclosure risk and prove its minimax optimality. It is nice because we close an open problem in the literature (20+ years!) and the optimality proof is kind of crazy (credits to Zachary). See paper here Read more
Bayesian nonparametric disclosure risk assessment Permalink
Published in Electronic Journal of Statistics, 2021
Stefano Favaro, Francesca Panero, Tommaso Rigon
In this paper we propose a Bayesian nonparametric estimator of disclosure risk. We find the posterior distribution of it, which is pretty cool. See paper here Read more
Achieving Fairness with a Simple Ridge Penalty Permalink
Published in Statistics and Computing, 2022
Marco Scutari, Francesca Panero, Manuel Proissl
In this paper we present a general framework for estimating regression models subject to a user-defined level of fairness. We do that using ridge regression, which is flexible, has already tons of literature and in general simplifies a lot the estimation. See paper here Read more
On sparsity, power-law and clustering properties of graphex processes Permalink
Published in Published in Advances of Applied Probability, 2023
François Caron, Francesca Panero and Judith Rousseau
This paper investigates properties of the class of graphs based on exchangeable point processes. We talk a lot about sparsity levels, degree distributions (power-law), positive clustering coefficients and central limit theorems. And we show how these properties hold for many many models. See paper here Read more
talks
teaching
ST449 - Artificial Intelligence
MSc course, London School of Economics, 2022
ST456 - Deep Learning
MSc course, London School of Economics, 2023
ST456 - Deep Learning
MSc course, London School of Economics, 2024
Probability and Stochastic Processes
MSc course, Sapienza University, 2024