%20methods%20for%20spatio-temporal%20forecasting%20fail%20to%20capture%20the%20inherent%20spatio-temporal%20heterogeneity%2C%20which%20calls%20for%20personalized%20FL%20(PFL)%20methods%20to%20model%20the%20spatio-temporally%20variant%20patterns.%20While%20contrastive%20learning%20approach%20is%20promising%20in%20addressing%20spatio-temporal%20heterogeneity%2C%20the%20existing%20methods%20are%20noneffective%20in%20determining%20negative%20pairs%20and%20can%20hardly%20apply%20to%20PFL%20paradigm.%20To%20tackle%20this%20limitation%2C%20we%20propose%20a%20novel%20PFL%20method%2C%20named%20Federated%20dUal%20sEmantic%20aLignment-based%20contraStive%20learning%20(FUELS)%2C%20which%20can%20adaptively%20align%20positive%20and%20negative%20pairs%20based%20on%20semantic%20similarity%2C%20thereby%20injecting%20precise%20spatio-temporal%20heterogeneity%20into%20the%20latent%20representation%20space%20by%20auxiliary%20contrastive%20tasks.%20From%20temporal%20perspective%2C%20a%20hard%20negative%20filtering%20module%20is%20introduced%20to%20dynamically%20align%20heterogeneous%20temporal%20representations%20for%20the%20supplemented%20intra-client%20contrastive%20task.%20From%20spatial%20perspective%2C%20we%20design%20lightweight-but-efficient%20prototypes%20as%20client-level%20semantic%20representations%2C%20based%20on%20which%20the%20server%20evaluates%20spatial%20similarity%20and%20yields%20client-customized%20global%20prototypes%20for%20the%20supplemented%20inter-client%20contrastive%20task.%20Extensive%20experiments%20demonstrate%20that%20FUELS%20outperforms%20state-of-the-art%20methods%2C%20with%20communication%20cost%20decreasing%20by%20around%2094%25.)
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