An Optimized Sparse Approximate Matrix Multiply for Matrices with Decay.
Nicolas BockMatt ChallacombePublished in: SIAM J. Sci. Comput. (2013)
Keyphrases
- coefficient matrix
- sparse matrix
- singular value decomposition
- low rank matrix
- linear systems
- binary matrices
- low rank and sparse
- low rank approximation
- floating point
- low rank matrices
- singular values
- systems of linear equations
- signal recovery
- square matrices
- positive definite
- perturbation theory
- singular vectors
- projection matrices
- low rank
- random projections
- block diagonal
- sparse matrices
- rows and columns
- negative matrix factorization
- measurement matrix
- interior point methods
- matrix representation
- data matrix
- binary matrix
- symmetric matrices
- projection matrix
- convex optimization
- pseudo inverse
- eigenvalues and eigenvectors
- linear algebra
- dimensionality reduction
- positive semidefinite
- nonnegative matrix factorization
- totally unimodular
- symmetric positive definite
- eigenvalue decomposition
- sufficient conditions
- matrix decomposition