Matrix multiplication via arithmetic progressions
Journal of Symbolic Computation - Special issue on computational algebraic complexity
Exploiting fast matrix multiplication within the level 3 BLAS
ACM Transactions on Mathematical Software (TOMS)
Locality of Reference in LU Decomposition with Partial Pivoting
SIAM Journal on Matrix Analysis and Applications
Recursion leads to automatic variable blocking for dense linear-algebra algorithms
IBM Journal of Research and Development
Introduction to Algorithms
Straight monotonic embedding of data sets in Euclidean spaces
Neural Networks
Experiments with Quadtree Representation of Matrices
ISAAC '88 Proceedings of the International Symposium ISSAC'88 on Symbolic and Algebraic Computation
Computing generalized inverses using LU factorization of matrix product
International Journal of Computer Mathematics
Minimal-storage high-performance Cholesky factorization via blocking and recursion
IBM Journal of Research and Development
| Hi-index | 7.30 |
Starting from the Strassen method for rapid matrix multiplication and inversion as well as from the recursive Cholesky factorization algorithm, we introduced a completely block recursive algorithm for generalized Cholesky factorization of a given symmetric, positive semi-definite matrix A@?R^n^x^n. We used the Strassen method for matrix inversion together with the recursive generalized Cholesky factorization method, and established an algorithm for computing generalized {2,3} and {2,4} inverses. Introduced algorithms are not harder than the matrix-matrix multiplication.