1 citations · 1 across the 4 of their papers we have counts for
4 papers
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-…
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…
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…
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…