Dozens of machine learning algorithms require computing the inverse of a matrix. Computing a matrix inverse is conceptually easy, but implementation is one of the most challenging tasks in numerical ...

The properties of the maximum likelihood estimate of the parameter of a first-order moving-average model, depend on the inverse of a symmetric tridiagonal matrix. Hitherto, approximate expressions for ...