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cs.LG2024
Concurrent vertical and horizontal federated learning with fuzzy cognitive maps
Jose L Salmeron, Irina Arévalo
Data privacy is a major concern in industries such as healthcare or finance. The requirement to safeguard privacy is essential to prevent data breaches and misuse, which can have s…
cs.LG2024
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…
cs.LG2024
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…