A Fast Relaxation Method for Computing a Column of the Matrix Exponential of Stochastic Matrices from Large, Sparse Networks.
Kyle KlosterDavid F. GleichPublished in: CoRR (2013)
Keyphrases
- coefficient matrix
- binary matrices
- rows and columns
- sparse matrix
- data matrix
- binary matrix
- singular value decomposition
- jump diffusion process
- low rank approximation
- sparse matrices
- low rank matrix
- linear algebra
- missing values
- low rank matrices
- low rank and sparse
- projection matrices
- linear systems
- singular values
- low rank
- singular vectors
- eigenvalues and eigenvectors
- signal recovery
- matrix factorization
- social networks
- matrix representation
- tensor factorization
- square matrices
- systems of linear equations
- positive definite
- projection matrix
- original data
- pseudo inverse
- matrix completion
- block diagonal
- hopfield neural network
- eigenvalue decomposition
- barcode
- negative matrix factorization
- efficient computation
- gene expression data
- symmetric matrices
- covariance matrix
- network structure
- sparse representation