Tipo di tesi
Tesi di laurea magistrale
Titolo
Federated Echo State Neural Networks with Exact Decentralized Consensus
Corso di studi
INFORMATICA
Parole chiave
- Decentralized Federated Learning
- Echo State Networks
- Federated Learning
- Pervasive Computing
Data inizio appello
01/12/2023
Consultabilità
Non consultabile
Data di rilascio
01/12/2093
Riassunto (Italiano)
Federated Echo State Networks proved their efficiency in learning low-resource collaborative settings where data is regulated privacy. In this thesis, we broaden the applicability of this machine learning approach to a decentralized setting, where multiple agents collaborate to learn a global readout with a one-shot, exact consensus mechanism. Experiments prove the efficacy and the efficiency of the proposed learning methodology against a state-of-the-art competitor on multiple benchmarks, characterized by different levels of statistical heterogeneity.
