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 difficult tasks in numerical ...

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 ...

It is well known that the correlation matrix has a central role in the analysis of multivariate data. The inverse of the correlation matrix, however, also has important interpretations. An exposition ...

For a symmetric correlation matrix, the Inverse Correlation Matrix table contains the inverse of the correlation matrix, as shown in Figure 40.14. The diagonal elements of the inverse correlation ...

We suggest a method for estimating a covariance matrix on the basis of a sample of vectors drawn from a multivariate normal distribution. In particular, we penalize the likelihood with a lasso penalty ...