149 citations · 153 across the 8 of their papers we have counts for
4 papers · 1 filter
Improving -Byzantine Resilience in Federated Learning via layerwise aggregation and cosine distance
Mario García-Márquez, Nuria Rodríguez-Barroso, M. Victoria Luzón +1
The rapid development of artificial intelligence systems has amplified societal concerns regarding their usage, necessitating regulatory frameworks that encompass data privacy. Fed…
Krum Federated Chain (KFC): Using blockchain to defend against adversarial attacks in Federated Learning
Mario García-Márquez, Nuria Rodríguez-Barroso, M. Victoria Luzón +1
Federated Learning presents a nascent approach to machine learning, enabling collaborative model training across decentralized devices while safeguarding data privacy. However, its…
An Interpretable Client Decision Tree Aggregation process for Federated Learning
Alberto Argente-Garrido, Cristina Zuheros, M. Victoria Luzón +1
Trustworthy Artificial Intelligence solutions are essential in today's data-driven applications, prioritizing principles such as robustness, safety, transparency, explainability, a…
Federated Learning and Differential Privacy: Software tools analysis, the Sherpa.ai FL framework and methodological guidelines for preserving data privacy
Nuria Rodríguez-Barroso, Goran Stipcich, Daniel Jiménez-López +6
The high demand of artificial intelligence services at the edges that also preserve data privacy has pushed the research on novel machine learning paradigms that fit those requirem…