Raouf Kerkouche

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 20

Top Topics

Gene Expression

Biologically Plausible

Differentially Private

Top Venues

Publications

Hui-Po Wang, Dingfan Chen, Raouf Kerkouche, Mario Fritz
FedLAP-DP: Federated Learning by Sharing Differentially Private Loss Approximations. Proc. Priv. Enhancing Technol. 2024 (3) (2024)
Dingfan Chen, Raouf Kerkouche, Mario Fritz
A Unified View of Differentially Private Deep Generative Modeling. Trans. Mach. Learn. Res. 2024 (2024)
Dingfan Chen, Marie Oestreich, Tejumade Afonja, Raouf Kerkouche, Matthias Becker, Mario Fritz
Towards Biologically Plausible and Private Gene Expression Data Generation. CoRR (2024)
Shadi Rahimian, Raouf Kerkouche, Ina Kurth, Mario Fritz
Private and Collaborative Kaplan-Meier Estimators. CoRR (2023)
Dingfan Chen, Raouf Kerkouche, Mario Fritz
A Unified View of Differentially Private Deep Generative Modeling. CoRR (2023)
Rubèn Tito, Khanh Nguyen, Marlon Tobaben, Raouf Kerkouche, Mohamed Ali Souibgui, Kangsoo Jung, Lei Kang, Ernest Valveny, Antti Honkela, Mario Fritz, Dimosthenis Karatzas
Privacy-Aware Document Visual Question Answering. CoRR (2023)
Raouf Kerkouche, Gergely Ács, Mario Fritz
Client-specific Property Inference against Secure Aggregation in Federated Learning. WPES@CCS (2023)
Raouf Kerkouche, Gergely Ács, Mario Fritz
Client-specific Property Inference against Secure Aggregation in Federated Learning. CoRR (2023)
Hui-Po Wang, Dingfan Chen, Raouf Kerkouche, Mario Fritz
Fed-GLOSS-DP: Federated, Global Learning using Synthetic Sets with Record Level Differential Privacy. CoRR (2023)
Shadi Rahimian, Raouf Kerkouche, Ina Kurth, Mario Fritz
Practical Challenges in Differentially-Private Federated Survival Analysis of Medical Data. CHIL (2022)
Shadi Rahimian, Raouf Kerkouche, Ina Kurth, Mario Fritz
Practical Challenges in Differentially-Private Federated Survival Analysis of Medical Data. CoRR (2022)
Dingfan Chen, Raouf Kerkouche, Mario Fritz
Private Set Generation with Discriminative Information. NeurIPS (2022)
Dingfan Chen, Raouf Kerkouche, Mario Fritz
Private Set Generation with Discriminative Information. CoRR (2022)
Raouf Kerkouche, Gergely Ács, Claude Castelluccia, Pierre Genevès
Compression Boosts Differentially Private Federated Learning. EuroS&P (2021)
Raouf Kerkouche, Gergely Ács, Claude Castelluccia, Pierre Genevès
Constrained differentially private federated learning for low-bandwidth devices. UAI (2021)
Raouf Kerkouche, Gergely Ács, Claude Castelluccia, Pierre Genevès
Privacy-preserving and bandwidth-efficient federated learning: an application to in-hospital mortality prediction. CHIL (2021)
Raouf Kerkouche, Gergely Ács, Claude Castelluccia, Pierre Genevès
Constrained Differentially Private Federated Learning for Low-bandwidth Devices. CoRR (2021)
Raouf Kerkouche, Gergely Ács, Claude Castelluccia
Federated Learning in Adversarial Settings. CoRR (2020)
Raouf Kerkouche, Gergely Ács, Claude Castelluccia, Pierre Genevès
Compression Boosts Differentially Private Federated Learning. CoRR (2020)
Raouf Kerkouche, Réda Alami, Raphaël Féraud, Nadège Varsier, Patrick Maillé
Node-based optimization of LoRa transmissions with Multi-Armed Bandit algorithms. ICT (2018)