Svd, Dropout Regularization, Portfolio Management.
matrix [2]. Equation (1) is projection of M onto the vector space spanned by its eigenvectors. It can be rewritten as: Similarly, M as a linear function can be written as: In the left hand side of Figure 1, we see how a symmetric matrix transforms a given vector x in the 2D plane and on the right