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This document presents a novel tensor-response regression model that incorporates covariates across multiple modes, addressing challenges found in neuroimaging, network analysis, and spatial-temporal modeling. The proposed method allows for high-dimensional tensor responses and covariate matrices, utilizing an efficient alternating updating algorithm and demonstrating superior performance through simulations and real data applications. The model is designed to identify variations in tensor data explained by

Author

yingjiaxi

Language

EN