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cs.LG2025
From Dense to Sparse: Event Response for Enhanced Residential Load Forecasting
Xin Cao, Qinghua Tao, Yingjie Zhou +5
Residential load forecasting (RLF) is crucial for resource scheduling in power systems. Most existing methods utilize all given load records (dense data) to indiscriminately extrac…
cs.LG2024★ 2 cited
Towards Optimal Customized Architecture for Heterogeneous Federated Learning with Contrastive Cloud-Edge Model Decoupling
Xingyan Chen, Tian Du, Mu Wang +5
Federated learning, as a promising distributed learning paradigm, enables collaborative training of a global model across multiple network edge clients without the need for central…