Svd, Dropout Regularization, Portfolio Management.
are not orthogonal. Symmetric Matrices are eigendecomposable. It means for any symmetric matrix M with eigenvalues λ_1, …, λ_n and eigenvectors u_1, …, u_n: For example: Check out Wolfram Alpha, an online tool that generate eigenvalues and eigenvectors in addition to other identifiers for a given