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Sylvain Chatel

This person is no longer with EPFL

Related publications (6)

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Thwarting Malicious Adversaries in Homomorphic Encryption Pipelines

Sylvain Chatel

Homomorphic Encryption (HE) enables computations to be executed directly on encrypted data. As such, it is an auspicious solution for protecting the confidentiality of sensitive data without impeding its usability. However, HE does not provide any guarante ...

EPFL2023

Verifiable Encodings for Secure Homomorphic Analytics

Jean-Pierre Hubaux, Sylvain Chatel, Apostolos Pyrgelis, Christian Louis Knabenhans

Homomorphic encryption, which enables the execution of arithmetic operations directly on ciphertexts, is a promising solution for protecting privacy of cloud-delegated computations on sensitive data. However, the correctness of the computation result is no ...

2022

Privacy and Integrity Preserving Computations with CRISP

Jean-Pierre Hubaux, Juan Ramón Troncoso-Pastoriza, Sylvain Chatel, Apostolos Pyrgelis

In the digital era, users share their personal data with service providers to obtain some utility, e.g., access to high-quality services. Yet, the induced information flows raise privacy and integrity concerns. Consequently, cautious users may want to prot ...

USENIX ASSOC2021

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In this paper, we present a reproduction of the paper of Bertinetto et al. [2019] "Meta-learning with differentiable closed-form solvers" as part of the ICLR 2019 Reproducibility Challenge. In successfully reproducing the most crucial part of the paper, we ...

2019

[Re] Meta learning with differentiable closed-form solvers

Matthias Grossglauser, Sylvain Chatel, Arnout Jan J Devos

In this work, we present a reproduction of the paper of Bertinetto et al. ”Meta- learning with differentiable closed-form solvers” as part of the ICLR 2019 Reproducibility Challenge. In successfully reproducing the most crucial part of the paper, we reach ...

2019

[Re] Meta-learning with differentiable closed-form solvers

Matthias Grossglauser, Sylvain Chatel

2019