Svd, Dropout Regularization, Portfolio Management.
…, λ_n be eigenvalues of M’M. Then M’s Singular Values σ_1, …, σ_n are defined as : We are now prepared to introduce  (SVD). Any Matrix M with singular values σ_1, …, σ_n, can be decompose to: And similar to Equation (3): Figure 2 from [1] gives a great visualization of SVD inner working. Figure 2: