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R. Kerkouche · SciRah

Researcher profile · Semantic Scholar

R. Kerkouche

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R. Kerkouche — researcher profile on SciRah

h-index: 10
Works: 22
Citations: 322

Most-cited papers

Privacy-preserving and bandwidth-efficient federated learning: an application to in-hospital mortality prediction
R. Kerkouche, Gergely Ács, C. Castelluccia, P. Genevès
2021ACM Conference on Health, Inference, and Learning60 citations Open access
Semantic Scholar
Private Set Generation with Discriminative Information
Dingfan Chen, R. Kerkouche, Mario Fritz
2022Neural Information Processing Systems51 citations Open access
Semantic Scholar
Compression Boosts Differentially Private Federated Learning
R. Kerkouche, Gergely Ács, C. Castelluccia, P. Genevès
2020European Symposium on Security and Privacy39 citations Open access
Semantic Scholar
Node-based optimization of LoRa transmissions with Multi-Armed Bandit algorithms
R. Kerkouche, Réda Alami, Raphaël Féraud, N. Varsier +1 more
2018International Conference on Telecommunications38 citations Open access
Semantic Scholar
Privacy-Aware Document Visual Question Answering
Rubèn Pérez Tito, K. Nguyen, Marlon Tobaben, R. Kerkouche +10 more
2023IEEE International Conference on Document Analysis and Recognition20 citations
Semantic Scholar
Practical Challenges in Differentially-Private Federated Survival Analysis of Medical Data
Shadi Rahimian, R. Kerkouche, I. Kurth, Mario Fritz
2022ACM Conference on Health, Inference, and Learning19 citations
Semantic Scholar
Federated Learning in Adversarial Settings
R. Kerkouche, Gergely Ács, C. Castelluccia
2020arXiv.org19 citations
Semantic Scholar
Client-specific Property Inference against Secure Aggregation in Federated Learning
R. Kerkouche, Gergely Ács, Mario Fritz
2023WPES@CCS16 citations Open access
Semantic Scholar
Towards Biologically Plausible and Private Gene Expression Data Generation
Dingfan Chen, Marie Oestreich, Tejumade Afonja, R. Kerkouche +2 more
2024Proceedings on Privacy Enhancing Technologies11 citations
Semantic Scholar
Constrained Differentially Private Federated Learning for Low-bandwidth Devices
R. Kerkouche, Gergely Ács, C. Castelluccia, P. Genevès
2021Conference on Uncertainty in Artificial Intelligence11 citations
Semantic Scholar
FedLAP-DP: Federated Learning by Sharing Differentially Private Loss Approximations
Hui-Po Wang, Dingfan Chen, R. Kerkouche, Mario Fritz
2023Proceedings on Privacy Enhancing Technologies9 citations Open access
Semantic Scholar
DP-2Stage: Adapting Language Models as Differentially Private Tabular Data Generators
Tejumade Afonja, Hui-Po Wang, R. Kerkouche, Mario Fritz
2024Trans. Mach. Learn. Res.8 citations
Semantic Scholar
A Unified View of Differentially Private Deep Generative Modeling
Dingfan Chen, R. Kerkouche, Mario Fritz
2023Trans. Mach. Learn. Res.6 citations Open access
Semantic Scholar
Private and Collaborative Kaplan-Meier Estimators
Shadi Rahimian, R. Kerkouche, I. Kurth, Mario Fritz
2023WPES@CCS6 citations Open access
Semantic Scholar
NeurIPS 2023 Competition: Privacy Preserving Federated Learning Document VQA
Marlon Tobaben, Mohamed Ali Souibgui, Rubèn Pérez Tito, K. Nguyen +23 more
2024Trans. Mach. Learn. Res.4 citations
Semantic Scholar
DocMIA: Document-Level Membership Inference Attacks against DocVQA Models
K. Nguyen, R. Kerkouche, Mario Fritz, D. Karatzas
2025International Conference on Learning Representations2 citations
Semantic Scholar
Differentially private federated learning for localized control of infectious disease dynamics
R. Kerkouche, H. Zunker, Mario Fritz, M. Kühn
2025Scientific Reports2 citations Open access
Semantic Scholar
Differentially Private Federated Learning for Bandwidth and Energy Constrained Environments. (Apprentissage fédéré avec confidentialité différentielle pour les environnements contraints en bande passante et énergie)
R. Kerkouche
20212 citations Open access
Semantic Scholar
An Exploratory Survey Study Toward a Conceptual Framework for Structuring the Integration of Privacy-Enhancing Technologies in Federated Learning and Analytics
Hammam Abu Attieh, Mehmed Halilovic, R. Kerkouche, Shadi Rahimian +10 more
2026IEEE Access1 citations Open access
Semantic Scholar
Predicting COVID-19 incidence from seroprevalence and population-based cohort data using interpretable machine learning with differential privacy analysis
J. Krepel, R. Binkytė, R. Kerkouche, M. Harries +6 more
2026medRxiv0 citations Open access
Semantic Scholar
Proceedings of the Third Workshop on Privacy in Natural Language Processing
Om Thakkar, Swaroop Indra Ramaswamy, Rajiv Mathews, Franoise Beaufays +496 more
20210 citations Open access
Semantic Scholar
DP-2Stage: Adapting Language Models as Di ! erentially Private Tabular Data Generators
Tejumade Afonja, Hui-Po Wang, R. Kerkouche, Mario Fritz
0 citations
Semantic Scholar

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