Abstract: Personalized federated learning (pFL) is to collaboratively train non-identical machine learning models for different clients to adapt to their heterogeneously distributed datasets. State-of ...
Abstract: Unmanned aerial vehicles (UAVs) have gained significant attention in practical applications, especially the low-altitude aerial (LAA) object detection imposes stringent requirements on ...
The paper benchmarks tree-based models (Random Forest, LightGBM, XGBoost) against deep learning (LSTM, CNN-LSTM, GRU, TFT) for hourly building electricity load forecasting, and demonstrates that ...
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