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A Higher-Order Generalized Singular Value Decomposition for Rank-Deficient Matrices
.The higher-order generalized singular value decomposition (HO-GSVD) is a matrix factorization technique that extends the GSVD to \(N \ge 2\) data matrices and can be used to identify common subspaces that are shared across multiple large-scale datasets with different row dimensions. The standard HO-GSVD factors \(N\) matrices \(A_i\in \mathbb{R}^{m_i\times n}\) …