A concise reference on advanced matrix theory, including: <\/p>\n
\u2022 an easy way to compute matrix derivatives and second derivatives
\n\u2022 a general framework for inverting partitioned matrices
\n\u2022 useful properties of Kronecker product, Hadamard product, and diag
\n\u2022 the column-stacking operator “vec” and its generalization to “vec-transpose” <\/p>\n
with applications to multilinear models, principal component analysis, blind source separation, Lyapunov equations, model alignment, and more.<\/p>\n","protected":false},"excerpt":{"rendered":"
A concise reference on advanced matrix theory, including: \u2022 an easy way to compute matrix derivatives and second derivatives \u2022 a general framework for inverting partitioned matrices \u2022 useful properties of Kronecker product, Hadamard product, and diag \u2022 the column-stacking operator “vec” and its generalization to “vec-transpose” with applications to multilinear models, principal component analysis, 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