Federated Learning for Time Series Forecasting Using Hybrid Model

Federated Learning for Time Series Forecasting Using Hybrid Model

Time Series data has become ubiquitous thanks to affordable edge devices and sensors. Much of this data is valuable for decision making. In order to use these data for the forecasting task, the conventional centralized approach has shown deficiencies regarding large data communication and data priva...

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Bibliographic Details
Main Author: Li, Yuntao
Format: Others
Language:English
Published: KTH, Skolan för elektroteknik och datavetenskap (EECS) 2019
Subjects:
Federated Learning
Time Series Forecasting
Recurrent Neural Networks
Long Short-Term Memory
Hybrid Model
Federerad Inlärning
Tidsserieprognostisering
Återkommande Neurala Nätverk
LSTMs
Hybrida Modeller
Computer and Information Sciences
Data- och informationsvetenskap
Online Access:http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-254677

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http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-254677

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