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T. LaPorta

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#machine learning Preprint Aug 2026

Initialization Is Critical: Advancing Federated Short-Term Load Forecasting under Load Heterogeneity via Model Initialization

This paper studies the role of model initialization in federated STLF, and proposes two initialization strategies from global and local perspectives, which effectively improve forecasting performance, as evidenced by reduced client drift, improved convergence behavior, and lower forecasting errors.

Jia-Ning Chen, Vajiheh Farhadi, Yan Li et al. · 0 citations