output
20212026
most citedNo more glowing in the dark: How deep learning improves exposure date estimation in thermoluminescence dosimetry

12 citations

5 papers

cs.DC2026

Stream Learning: Partition-Fair Gossip Learning Without Tokens

Fabien Mathieu, Alexandre Pham, Maria Gradinariu Potop-Butucaru +1

In gossip learning, a network of nodes trains a shared model collaboratively, without a central coordinator, by repeatedly exchanging parts of their local models. The state-of-the-…

cs.CR2026

LIFT: Byzantine Resilient Hub-Sampling

Mohamed Amine Legheraba, Nour Rachdi, Maria Gradinariu Potop-Butucaru +1

Recently, a novel peer sampling protocol, Elevator, was introduced to construct network topologies tailored for emerging decentralized applications such as federated learning and b…

cs.DC2024★ 1 cited

Emergent Peer-to-Peer Multi-Hub Topology

Mohamed Amine Legheraba, Maria Potop-Butucaru, Sébastien Tixeuil +1

In this paper we propose and evaluate an innovative algorithm that enables the creation of Peer-to-Peer network overlays characterized by emergent multi-hubs. This approach generat…

cs.DC2024

Data Poisoning Attacks in Gossip Learning

Alexandre Pham, Maria Potop-Butucaru, Sébastien Tixeuil +1

Traditional machine learning systems were designed in a centralized manner. In such designs, the central entity maintains both the machine learning model and the data used to adjus…

physics.med-ph2021★ 12 cited

No more glowing in the dark: How deep learning improves exposure date estimation in thermoluminescence dosimetry

Florian Mentzel, Evelin Derugin, Hannah Jansen +4

The time- or temperature-resolved detector signal from a thermoluminescence dosimeter can reveal additional information about circumstances of an exposure to ionizing irradiation.…