Linear discriminant analysis (LDA) is a well-known scheme for feature extraction and dimensionality reduction of labeled data in a vector space. Recently, LDA has been extended to...
Versus the customary preconditioners, our weakly random ones are generated more readily and for a much larger class of input matrices. Furthermore our preconditioners have a wider...
Victor Y. Pan, Dmitriy Ivolgin, Brian Murphy, Rhys...
The nested dissection method developed by Lipton, Rose, and Tarjan is a seminal method for quickly performing Gaussian elimination of symmetric real positive definite matrices who...
Abstract. We investigate the performance of two approaches for matrix inversion based on Gaussian (LU factorization) and Gauss-Jordan eliminations. The target architecture is a cur...
Peter Benner, Pablo Ezzatti, Enrique S. Quintana-O...
Many scientific and engineering applications involve inverting large matrices or solving systems of linear algebraic equations. Solving these problems with proven algorithms for d...
Simon Branford, Cihan Sahin, Ashish Thandavan, Chr...