Minimum Degree Reordering Algorithms: A Tutorial

The problem of matrix inversion is central to many applications of Numerical Linear Algebra. When the matrix to invert is dense, little can be done to avoid the costly O(n 3) process of Gaussian Elimination. When the matrix is symmetric, one can use the Cholesky Factorization to reduce the work of inversion (still O(n 3), but with a smaller coefficient). When the matrix is both sparse and symmetric, we have even mor