The H2020 TEACHING project puts forward a human-centered vision for adapting and optimising autonomous applications, leveraging users' physiological, emotional and cognitive states. Such a goal can be achieved by building a distributed, embedded and federated learning system complemented by methods and tools to enforce its dependability, security, and privacy preservation.

Supporting privacy preservation by distributed and federated learning on the edge

Dazzi P;Gotta A
2021

Abstract

The H2020 TEACHING project puts forward a human-centered vision for adapting and optimising autonomous applications, leveraging users' physiological, emotional and cognitive states. Such a goal can be achieved by building a distributed, embedded and federated learning system complemented by methods and tools to enforce its dependability, security, and privacy preservation.
2021
Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo" - ISTI
Inglese
127
38
39
2
https://ercim-news.ercim.eu/en127/r-i/supporting-privacy-preservation-by-distributed-and-federated-learning-on-the-edge
Distributed learning
Federated learning
3
info:eu-repo/semantics/article
262
Bacciu, D; Dazzi, P; Gotta, A
01 Contributo su Rivista::01.01 Articolo in rivista
open
   A computing toolkit for building efficient autonomous applications leveraging humanistic intelligence
   TEACHING
   H2020
   871385
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/447204
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