1 citations · 1 across the 3 of their papers we have counts for
4 papers
Dynamic Topology Optimization for Non-IID Data in Decentralized Learning
Bart Cox, Antreas Ioannou, Jérémie Decouchant
Decentralized learning (DL) enables a set of nodes to train a model collaboratively without central coordination, offering benefits for privacy and scalability. However, DL struggl…
Go With The Flow: Churn-Tolerant Decentralized Training of Large Language Models
Nikolay Blagoev, Bart Cox, Jérémie Decouchant +1
Motivated by the emergence of large language models (LLMs) and the importance of democratizing their training, we propose GWTF, the first crash tolerant practical decentralized tra…
Reliable Communication in Hybrid Authentication and Trust Models
Rowdy Chotkan, Bart Cox, Vincent Rahli +1
Reliable communication is a fundamental distributed communication abstraction that allows any two nodes of a network to communicate with each other. It is necessary for more powerf…
Training Diffusion Models with Federated Learning
Matthijs de Goede, Bart Cox, Jérémie Decouchant
The training of diffusion-based models for image generation is predominantly controlled by a select few Big Tech companies, raising concerns about privacy, copyright, and data auth…