Schmidt-Mirsky matrix approximation with linearly constrained singular values

Schmidt and Mirskyʹs theorems identify the matrix with a specified rank that lies closest to another matrix, with distances measured by any matrix norm invariant under the unitary group. The more general result presented here identifies the nearest matrix whose singular values satisfy any specified set of linear constraints. A typical application consists in determining the oblate spheroid that most closely fits a specified ellipsoid.