Personalized Federated DARTS for Electricity Load Forecasting of Individual Buildings
Author:
Affiliation:
1. Department of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong, China
2. DAMO Academy, Alibaba Group (U.S.) Inc., Bellevue, WA, USA
3. DAMO Academy, Group, Hangzhou, China
Funder
National Key Research and Development Program of China
National Natural Science Foundation of China
Alibaba Innovative Research Programme
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
General Computer Science
Link
http://xplorestaging.ieee.org/ielx7/5165411/10288469/10063999.pdf?arnumber=10063999
Reference38 articles.
1. Deep-Based Conditional Probability Density Function Forecasting of Residential Loads
2. Long Short-Term Memory
3. Short-Term Load Forecasting With Deep Residual Networks
4. DARTS+: Improved differentiable architecture search with early stopping;liang;arXiv 1909 06035,2019
5. Incorporating Practice Theory in Sub-Profile Models for Short Term Aggregated Residential Load Forecasting
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