3 citations · 3 across the 3 of their papers we have counts for
3 papers
Decentralized Federated Learning of Probabilistic Generative Classifiers
Aritz Pérez, Carlos Echegoyen, Guzmán Santafé
Federated learning is a paradigm of increasing relevance in real world applications, aimed at building a global model across a network of heterogeneous users without requiring the…
Risk-based Calibration for Generative Classifiers
Aritz Pérez, Carlos Echegoyen, Guzmán Santafé
Generative classifiers are constructed on the basis of a joint probability distribution and are typically learned using closed-form procedures that rely on data statistics and maxi…
Large-scale unsupervised spatio-temporal semantic analysis of vast regions from satellite images sequences
Carlos Echegoyen, Aritz Pérez, Guzmán Santafé +2
Temporal sequences of satellite images constitute a highly valuable and abundant resource for analyzing regions of interest. However, the automatic acquisition of knowledge on a la…