Dr. James McCaffrey of Microsoft Research presents a full-code, step-by-step tutorial on an implementation of the technique that emphasizes simplicity and ease-of-modification over robustness and ...

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 ...

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 ...

Journal of Applied Probability, Vol. 27, No. 1 (Mar., 1990), pp. 156-170 (15 pages) Let Xt be a discrete-time multivariate stationary process possessing an infinite autoregressive representation and ...

We introduce a new sparse sliced inverse regression estimator called Cholesky matrix penalization, and its adaptive version, for achieving sparsity when estimating the dimensions of a central subspace ...