Zobrazeno 1 - 10
of 4 396
pro vyhledávání: '"de Cristofaro A"'
Autor:
Conti, Mauro, De Cristofaro, Emiliano, Galeazzi, Alessandro, Paudel, Pujan, Stringhini, Gianluca
Online social media platforms significantly influence public debates by shaping the information users encounter. Content visibility on these platforms is regulated by recommendation algorithms designed to maximize user engagement using individual-lev
Externí odkaz:
http://arxiv.org/abs/2410.17390
Synthetic data created by differentially private (DP) generative models is increasingly used in real-world settings. In this context, PATE-GAN has emerged as a popular algorithm, combining Generative Adversarial Networks (GANs) with the private train
Externí odkaz:
http://arxiv.org/abs/2406.13985
Federated Learning (FL) has emerged as a solution for distributed systems that allow clients to train models on their data and only share models instead of local data. Generative Models are designed to learn the distribution of a dataset and generate
Externí odkaz:
http://arxiv.org/abs/2405.16682
This paper presents an auditing procedure for the Differentially Private Stochastic Gradient Descent (DP-SGD) algorithm in the black-box threat model that is substantially tighter than prior work. The main intuition is to craft worst-case initial mod
Externí odkaz:
http://arxiv.org/abs/2405.14106
Differentially private synthetic data generation (DP-SDG) algorithms are used to release datasets that are structurally and statistically similar to sensitive data while providing formal bounds on the information they leak. However, bugs in algorithm
Externí odkaz:
http://arxiv.org/abs/2405.10994
Online web communities often face bans for violating platform policies, encouraging their migration to alternative platforms. This migration, however, can result in increased toxicity and unforeseen consequences on the new platform. In recent years,
Externí odkaz:
http://arxiv.org/abs/2405.10233
Autor:
Efstratiou, Alexandros, Efstratiou, Marina, Yudhoatmojo, Satrio, Blackburn, Jeremy, De Cristofaro, Emiliano
The COVID-19 pandemic brought about an extraordinary rate of scientific papers on the topic that were discussed among the general public, although often in biased or misinformed ways. In this paper, we present a mixed-methods analysis aimed at examin
Externí odkaz:
http://arxiv.org/abs/2401.13248
Autor:
Papadamou, Kostantinos, Patel, Jay, Blackburn, Jeremy, Jovanovic, Philipp, De Cristofaro, Emiliano
This paper presents a large-scale analysis of the cryptocurrency community on Reddit, shedding light on the intricate relationship between the evolution of their activity, emotional dynamics, and price movements. We analyze over 130M posts on 122 cry
Externí odkaz:
http://arxiv.org/abs/2312.08394
Autor:
Ganev, Georgi, De Cristofaro, Emiliano
Training generative models to produce synthetic data is meant to provide a privacy-friendly approach to data release. However, we get robust guarantees only when models are trained to satisfy Differential Privacy (DP). Alas, this is not the standard
Externí odkaz:
http://arxiv.org/abs/2312.05114
Autor:
Giulia Battafarano, Stefano Lancellotti, Monica Sacco, Michela Rossi, Sara Terreri, Jacopo Di Gregorio, Laura Di Giuseppe, Matteo D’Agostini, Ottavia Porzio, Leonardo Di Gennaro, Maira Tardugno, Simone Pelle, Salvatore Minisola, Renato Maria Toniolo, Matteo Luciani, Andrea Del Fattore, Raimondo De Cristofaro
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-14 (2024)
Abstract Haemophilia is associated with reduced bone mass and mineral density. Due to the rarity of the disease and the heterogeneity among the studies, the pathogenesis of bone loss is still under investigation. We studied the effects of coagulation
Externí odkaz:
https://doaj.org/article/a07d14be5e544bd38d8da6e3ba506cec
