Federated Transfer Learning for Energy Efficiency in Smart Buildings
Author:
Affiliation:
1. University of Murcia,Murcia,Spain
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10225747/10225748/10225844.pdf?arnumber=10225844
Reference30 articles.
1. Federated Learning: Challenges, Methods, and Future Directions
2. Client Selection and Bandwidth Allocation in Wireless Federated Learning Networks: A Long-Term Perspective
3. A transfer learning framework for predictive energy-related scenarios in smart buildings;gonzalez-vidal;IEEE Transactions on Industry Applications,2022
4. A Survey on Federated Learning: The Journey From Centralized to Distributed On-Site Learning and Beyond
5. Federated learning with matched averaging;wang;ArXiv Preprint,2020
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1. Transfer Learning for Day-Ahead Load Forecasting: A Case Study on European National Electricity Demand Time Series;Mathematics;2023-12-21
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