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This paper presents a novel multi-task learning framework for the accurate prediction of spatio-temporal data at multiple locations. The framework encodes the data as a third-order tensor and performs supervised tensor decomposition to identify the latent factors that capture the inherent spatiotemporal variabilities of the data and their relationship to the target variable of interest. The framework...
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