4 papers
Blind Federated Learning without initial model
Jose L. Salmeron, Irina Arévalo
Federated learning is an emerging machine learning approach that allows the construction of a model between several participants who hold their own private data. This method is sec…
A chaotic maps-based privacy-preserving distributed deep learning for incomplete and Non-IID datasets
Irina Arévalo, Jose L. Salmeron
Federated Learning is a machine learning approach that enables the training of a deep learning model among several participants with sensitive data that wish to share their own kno…
Benchmarking federated strategies in Peer-to-Peer Federated learning for biomedical data
Jose L. Salmeron, Irina Arévalo, Antonio Ruiz-Celma
The increasing requirements for data protection and privacy has attracted a huge research interest on distributed artificial intelligence and specifically on federated learning, an…
A characterization of the inclusions between mixed norm spaces
Irina Arévalo
We consider the mixed norm spaces of Hardy type studied by Flett and others. We study some properties of these spaces related to mean and pointwise growth and complement some parti…