Raouf Kerkouche

Orcid: 0000-0002-1458-7805

According to our database1, Raouf Kerkouche authored at least 18 papers between 2018 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

2018
2019
2020
2021
2022
2023
2024
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Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2024
A Unified View of Differentially Private Deep Generative Modeling.
Trans. Mach. Learn. Res., 2024

FedLAP-DP: Federated Learning by Sharing Differentially Private Loss Approximations.
Proc. Priv. Enhancing Technol., 2024

DP-2Stage: Adapting Language Models as Differentially Private Tabular Data Generators.
CoRR, 2024

NeurIPS 2023 Competition: Privacy Preserving Federated Learning Document VQA.
CoRR, 2024

Towards Biologically Plausible and Private Gene Expression Data Generation.
CoRR, 2024

Private and Collaborative Kaplan-Meier Estimators.
Proceedings of the 23rd Workshop on Privacy in the Electronic Society, 2024

Privacy-Aware Document Visual Question Answering.
Proceedings of the Document Analysis and Recognition - ICDAR 2024 - 18th International Conference, Athens, Greece, August 30, 2024

2023
Privacy-Aware Document Visual Question Answering.
CoRR, 2023

Fed-GLOSS-DP: Federated, Global Learning using Synthetic Sets with Record Level Differential Privacy.
CoRR, 2023

Client-specific Property Inference against Secure Aggregation in Federated Learning.
Proceedings of the 22nd Workshop on Privacy in the Electronic Society, 2023

2022
Private Set Generation with Discriminative Information.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Practical Challenges in Differentially-Private Federated Survival Analysis of Medical Data.
Proceedings of the Conference on Health, Inference, and Learning, 2022

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).
PhD thesis, 2021

Constrained differentially private federated learning for low-bandwidth devices.
Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

Compression Boosts Differentially Private Federated Learning.
Proceedings of the IEEE European Symposium on Security and Privacy, 2021

Privacy-preserving and bandwidth-efficient federated learning: an application to in-hospital mortality prediction.
Proceedings of the ACM CHIL '21: ACM Conference on Health, 2021

2020
Federated Learning in Adversarial Settings.
CoRR, 2020

2018
Node-based optimization of LoRa transmissions with Multi-Armed Bandit algorithms.
Proceedings of the 25th International Conference on Telecommunications, 2018


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