Fast randomized algorithms for structured matrices

Per-Gunnar Martinsson presents randomized black-box algorithms that compress rank-structured matrices, including H-matrices and HSS matrices, into data-sparse representations. Access is through matrix-vector products, which suits Schur-complement construction and matrix multiplication. When both the operator and its transpose admit O(N) application, the overall compression can also have linear complexity. A featured method combines compression and factorization of an H-matrix under strong admissibility.