Raouf Kerkouche

32 papers A* 2A 2Journal 21Unranked 6

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	An Exploratory Survey Study Toward a Conceptual Framework for Structuring the Integration of Privacy-Enhancing Technologies in Federated Learning and Analytics. IEEE Access Hammam Abu Attieh, Mehmed Halilovic, Raouf Kerkouche, Shadi Rahimian, Hui-Po Wang, Raphael Rehms, Georgios Kaissis, Alexander Ziller, Jonas Kuntzer, Karen Otte, Thierry Meurers, Mario Fritz, Daniel Rückert, Fabian Prasser
2025	J	`jnl`	DP-2Stage: Adapting Language Models as Differentially Private Tabular Data Generators. Trans. Mach. Learn. Res. Tejumade Afonja, Hui-Po Wang, Raouf Kerkouche, Mario Fritz
2025	J	`jnl`	Differentially private federated learning for localized control of infectious disease dynamics. CoRR Raouf Kerkouche, Henrik Zunker, Mario Fritz, Martin J. Kühn
2025	A*	`conf`	DocMIA: Document-Level Membership Inference Attacks against DocVQA Models. ICLR Khanh Nguyen, Raouf Kerkouche, Mario Fritz, Dimosthenis Karatzas
2025	J	`jnl`	DocMIA: Document-Level Membership Inference Attacks against DocVQA Models. CoRR Khanh Nguyen, Raouf Kerkouche, Mario Fritz, Dimosthenis Karatzas
2025	J	`jnl`	NeurIPS 2023 Competition: Privacy Preserving Federated Learning Document VQA. Trans. Mach. Learn. Res. Marlon Tobaben, Mohamed Ali Souibgui, Rubèn Tito, Khanh Nguyen, Raouf Kerkouche, Kangsoo Jung, Joonas Jälkö, Lei Kang, Andrey Barsky, Vincent Poulain D'Andecy, Aurélie Joseph, Aashiq Muhamed, Kevin Kuo, Virginia Smith, Yusuke Yamasaki, Takumi Fukami, Kenta Niwa, Iifan Tyou, Hiro Ishii, Rio Yokota, Ragul N, Rintu Kutum, Josep Lladós, Ernest Valveny, Antti Honkela, Mario Fritz, Dimosthenis Karatzas
2024	J	`jnl`	A Unified View of Differentially Private Deep Generative Modeling. Trans. Mach. Learn. Res. Dingfan Chen, Raouf Kerkouche, Mario Fritz
2024	J	`jnl`	DP-2Stage: Adapting Language Models as Differentially Private Tabular Data Generators. CoRR Tejumade Afonja, Hui-Po Wang, Raouf Kerkouche, Mario Fritz
2024	J	`jnl`	FedLAP-DP: Federated Learning by Sharing Differentially Private Loss Approximations. Proc. Priv. Enhancing Technol. Hui-Po Wang, Dingfan Chen, Raouf Kerkouche, Mario Fritz
2024	J	`jnl`	NeurIPS 2023 Competition: Privacy Preserving Federated Learning Document VQA. CoRR Marlon Tobaben, Mohamed Ali Souibgui, Rubèn Tito, Khanh Nguyen, Raouf Kerkouche, Kangsoo Jung, Joonas Jälkö, Lei Kang, Andrey Barsky, Vincent Poulain D'Andecy, Aurélie Joseph, Aashiq Muhamed, Kevin Kuo, Virginia Smith, Yusuke Yamasaki, Takumi Fukami, Kenta Niwa, Iifan Tyou, Hiro Ishii, Rio Yokota, Ragul N, Rintu Kutum, Josep Lladós, Ernest Valveny, Antti Honkela, Mario Fritz, Dimosthenis Karatzas
2024	—	`conf`	Privacy-Aware Document Visual Question Answering. ICDAR (6) Rubèn Tito, Khanh Nguyen, Marlon Tobaben, Raouf Kerkouche, Mohamed Ali Souibgui, Kangsoo Jung, Joonas Jälkö, Vincent Poulain D'Andecy, Aurélie Joseph, Lei Kang, Ernest Valveny, Antti Honkela, Mario Fritz, Dimosthenis Karatzas
2024	—	`conf`	Private and Collaborative Kaplan-Meier Estimators. WPES@CCS Shadi Rahimian, Raouf Kerkouche, Ina Kurth, Mario Fritz
2024	J	`jnl`	Towards Biologically Plausible and Private Gene Expression Data Generation. CoRR Dingfan Chen, Marie Oestreich, Tejumade Afonja, Raouf Kerkouche, Matthias Becker, Mario Fritz
2024	J	`jnl`	Towards Biologically Plausible and Private Gene Expression Data Generation. Proc. Priv. Enhancing Technol. Dingfan Chen, Marie Oestreich, Tejumade Afonja, Raouf Kerkouche, Matthias Becker, Mario Fritz
2023	J	`jnl`	A Unified View of Differentially Private Deep Generative Modeling. CoRR Dingfan Chen, Raouf Kerkouche, Mario Fritz
2023	—	`conf`	Client-specific Property Inference against Secure Aggregation in Federated Learning. WPES@CCS Raouf Kerkouche, Gergely Ács, Mario Fritz
2023	J	`jnl`	Client-specific Property Inference against Secure Aggregation in Federated Learning. CoRR Raouf Kerkouche, Gergely Ács, Mario Fritz
2023	J	`jnl`	Fed-GLOSS-DP: Federated, Global Learning using Synthetic Sets with Record Level Differential Privacy. CoRR Hui-Po Wang, Dingfan Chen, Raouf Kerkouche, Mario Fritz
2023	J	`jnl`	Privacy-Aware Document Visual Question Answering. CoRR Rubèn Tito, Khanh Nguyen, Marlon Tobaben, Raouf Kerkouche, Mohamed Ali Souibgui, Kangsoo Jung, Lei Kang, Ernest Valveny, Antti Honkela, Mario Fritz, Dimosthenis Karatzas
2023	J	`jnl`	Private and Collaborative Kaplan-Meier Estimators. CoRR Shadi Rahimian, Raouf Kerkouche, Ina Kurth, Mario Fritz
2022	—	`conf`	Practical Challenges in Differentially-Private Federated Survival Analysis of Medical Data. CHIL Shadi Rahimian, Raouf Kerkouche, Ina Kurth, Mario Fritz
2022	J	`jnl`	Practical Challenges in Differentially-Private Federated Survival Analysis of Medical Data. CoRR Shadi Rahimian, Raouf Kerkouche, Ina Kurth, Mario Fritz
2022	A*	`conf`	Private Set Generation with Discriminative Information. NeurIPS Dingfan Chen, Raouf Kerkouche, Mario Fritz
2022	J	`jnl`	Private Set Generation with Discriminative Information. CoRR Dingfan Chen, Raouf Kerkouche, Mario Fritz
2021	A	`conf`	Compression Boosts Differentially Private Federated Learning. EuroS&P Raouf Kerkouche, Gergely Ács, Claude Castelluccia, Pierre Genevès
2021	J	`jnl`	Constrained Differentially Private Federated Learning for Low-bandwidth Devices. CoRR Raouf Kerkouche, Gergely Ács, Claude Castelluccia, Pierre Genevès
2021	A	`conf`	Constrained differentially private federated learning for low-bandwidth devices. UAI Raouf Kerkouche, Gergely Ács, Claude Castelluccia, Pierre Genevès
2021	—	`—`	Differentially Private Federated Learning for Bandwidth and Energy Constrained Environments. (Apprentissage fédéré avec confidentialité différentielle pour les environnements contraints en bande passante et énergie). Raouf Kerkouche
2021	—	`conf`	Privacy-preserving and bandwidth-efficient federated learning: an application to in-hospital mortality prediction. CHIL Raouf Kerkouche, Gergely Ács, Claude Castelluccia, Pierre Genevès
2020	J	`jnl`	Compression Boosts Differentially Private Federated Learning. CoRR Raouf Kerkouche, Gergely Ács, Claude Castelluccia, Pierre Genevès
2020	J	`jnl`	Federated Learning in Adversarial Settings. CoRR Raouf Kerkouche, Gergely Ács, Claude Castelluccia
2018	—	`conf`	Node-based optimization of LoRa transmissions with Multi-Armed Bandit algorithms. ICT Raouf Kerkouche, Réda Alami, Raphaël Féraud, Nadège Varsier, Patrick Maillé