3652.1-2020 - IEEE guide for architectural framework and application of federated machine learning / / IEEE

• Pubblicazione: [Place of publication not identified] : , : IEEE, , 2021
• Descrizione fisica: 1 online resource
• Disciplina: 006.3
• Soggetto topico: Computational intelligence - Simulation methods; Machine learning - Mathematical models
• Sommario/riassunto: Federated machine learning defines a machine learning framework that allows a collective model to be constructed from data that is distributed across repositories owned by different organizations or devices. A blueprint for data usage and model building across organizations and devices while meeting applicable privacy, security and regulatory requirements is provided in this guide. It defines the architectural framework and application guidelines for federated machine learning, including description and definition of federated machine learning; the categories federated machine learning and the application scenarios to which each category applies; performance evaluation of federated machine learning; and associated regulatory requirements.
• Titolo autorizzato: 3652.1-2020 - IEEE Guide for Architectural Framework and Application of Federated Machine Learning
• ISBN: 1-5044-7053-2
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910445559703321
• Lo trovi qui: Univ. Federico II