activity
20202022
most citedPrivate Set Generation with Discriminative Information

14 citations · 22 across the 3 of their papers we have counts for

collaborators

5 papers

cs.CR202214 cited

Private Set Generation with Discriminative Information

Dingfan Chen, Raouf Kerkouche, Mario Fritz

Differentially private data generation techniques have become a promising solution to the data privacy challenge -- it enables sharing of data while complying with rigorous privacy…

cs.LG20226 cited

Practical Challenges in Differentially-Private Federated Survival Analysis of Medical Data

Shadi Rahimian, Raouf Kerkouche, Ina Kurth +1

Survival analysis or time-to-event analysis aims to model and predict the time it takes for an event of interest to happen in a population or an individual. In the medical context…

cs.CR20212 cited

Constrained Differentially Private Federated Learning for Low-bandwidth Devices

Raouf Kerkouche, Gergely Ács, Claude Castelluccia +1

Federated learning becomes a prominent approach when different entities want to learn collaboratively a common model without sharing their training data. However, Federated learnin…

cs.LG2020

Compression Boosts Differentially Private Federated Learning

Raouf Kerkouche, Gergely Ács, Claude Castelluccia +1

Federated Learning allows distributed entities to train a common model collaboratively without sharing their own data. Although it prevents data collection and aggregation by excha…

cs.CR2020

Federated Learning in Adversarial Settings

Raouf Kerkouche, Gergely Ács, Claude Castelluccia

Federated Learning enables entities to collaboratively learn a shared prediction model while keeping their training data locally. It prevents data collection and aggregation and, t…