GLSKF additively combines covariance-regularized low-rank tensor factorization with a locally correlated residual module under a generalized least squares objective for missing-data completion.
Tensor decompositions for signal processing applica- tions: From two-way to multiway component analysis,
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Generalized Least Squares Kernelized Tensor Factorization
GLSKF additively combines covariance-regularized low-rank tensor factorization with a locally correlated residual module under a generalized least squares objective for missing-data completion.