81 citations · 89 across the 4 of their papers we have counts for
4 papers
Non-IID data and Continual Learning processes in Federated Learning: A long road ahead
Marcos F. Criado, Fernando E. Casado, Roberto Iglesias +2
Federated Learning is a novel framework that allows multiple devices or institutions to train a machine learning model collaboratively while preserving their data private. This dec…
Concept drift detection and adaptation for federated and continual learning
Fernando E. Casado, Dylan Lema, Marcos F. Criado +3
Smart devices, such as smartphones, wearables, robots, and others, can collect vast amounts of data from their environment. This data is suitable for training machine learning mode…
Incremental Learning from Low-labelled Stream Data in Open-Set Video Face Recognition
Eric Lopez-Lopez, Carlos V. Regueiro, Xose M. Pardo
Deep Learning approaches have brought solutions, with impressive performance, to general classification problems where wealthy of annotated data are provided for training. In contr…
Federated and continual learning for classification tasks in a society of devices
Fernando E. Casado, Dylan Lema, Roberto Iglesias +2
Today we live in a context in which devices are increasingly interconnected and sensorized and are almost ubiquitous. Deep learning has become in recent years a popular way to extr…