RTPCA-SGD applies ScaledGD to t-SVD robust tensor PCA, claiming linear convergence independent of condition number, with a self-supervised deep-unfolded variant for learned parameters.
Matrix and tensor completion algorithms for background model initialization: A comparative evaluation,
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Learnable Scaled Gradient Descent for Guaranteed Robust Tensor PCA
RTPCA-SGD applies ScaledGD to t-SVD robust tensor PCA, claiming linear convergence independent of condition number, with a self-supervised deep-unfolded variant for learned parameters.