The paper defines a regularized three-factor low-rank decomposition and reports lower reconstruction error than SVD, but the comparison is inconsistent with the optimality of truncated SVD for fixed rank.
A penalized matrix decomposition, with applications to sparse principal components and canonical correlation analysis,
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Structured Variational $D$-Decomposition for Accurate and Stable Low-Rank Approximation
The paper defines a regularized three-factor low-rank decomposition and reports lower reconstruction error than SVD, but the comparison is inconsistent with the optimality of truncated SVD for fixed rank.