27 citations · 76 across the 20 of their papers we have counts for
6 papers · 1 filter
SYNAPSE: Framework for Neuron Analysis and Perturbation in Sequence Encoding
Jesús Sánchez Ochoa, Enrique Tomás Martínez Beltrán, Alberto Huertas Celdrán
In recent years, Artificial Intelligence has become a powerful partner for complex tasks such as data analysis, prediction, and problem-solving, yet its lack of transparency raises…
DMPA: Model Poisoning Attacks on Decentralized Federated Learning for Model Differences
Chao Feng, Yunlong Li, Yuanzhe Gao +4
Federated learning (FL) has garnered significant attention as a prominent privacy-preserving Machine Learning (ML) paradigm. Decentralized FL (DFL) eschews traditional FL's central…
S-VOTE: Similarity-based Voting for Client Selection in Decentralized Federated Learning
Pedro Miguel Sánchez Sánchez, Enrique Tomás Martínez Beltrán, Chao Feng +3
Decentralized Federated Learning (DFL) enables collaborative, privacy-preserving model training without relying on a central server. This decentralized approach reduces bottlenecks…
ProFe: Communication-Efficient Decentralized Federated Learning via Distillation and Prototypes
Pedro Miguel Sánchez Sánchez, Enrique Tomás Martínez Beltrán, Miguel Fernández Llamas +3
Decentralized Federated Learning (DFL) trains models in a collaborative and privacy-preserving manner while removing model centralization risks and improving communication bottlene…
FedEP: Tailoring Attention to Heterogeneous Data Distribution with Entropy Pooling for Decentralized Federated Learning
Chao Feng, Hongjie Guan, Alberto Huertas Celdrán +3
Non-Independent and Identically Distributed (non-IID) data in Federated Learning (FL) causes client drift issues, leading to slower convergence and reduced model performance. While…
De-VertiFL: A Solution for Decentralized Vertical Federated Learning
Alberto Huertas Celdrán, Chao Feng, Sabyasachi Banik +3
Federated Learning (FL), introduced in 2016, was designed to enhance data privacy in collaborative model training environments. Among the FL paradigm, horizontal FL, where clients…