Real-time forecasting of dietary habits and user health using Federated Learning with privacy guarantees

Real-time forecasting of dietary habits and user health using Federated Learning with privacy guarantees

Modern health self-monitoring devices and applications, such as Fitbit and MyFitnessPal, empower users to take concrete actions and set fitness and lifestyle goals based on their recorded trends and statistics. Predicting such trends is beneficial in the road of achieving long-time targets, as the i...

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Bibliographic Details
Main Author: Horchidan, Sonia-Florina
Format: Others
Language:English
Published: KTH, Skolan för elektroteknik och datavetenskap (EECS) 2020
Subjects:
Federated Learning
Time Series Forecasting
Clustering
Pattern Matching
Real-time Data Processing
Differential Privacy
Data Privacy.
Federerade Lärande
Tidsseriesprognos
Klustergruppering
Mönstermatchning
Realtidshantering av data
Differentialintegritet
Dataintegritet
Computer and Information Sciences
Data- och informationsvetenskap
Online Access:http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-281366

Internet

http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-281366

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