Online matrix prediction for sparse loss matrices.
Ken-ichiro MoridomiKohei HatanoEiji TakimotoKoji TsudaPublished in: ACML (2014)
Keyphrases
- coefficient matrix
- sparse matrix
- singular value decomposition
- low rank matrix
- low rank approximation
- low rank matrices
- prediction accuracy
- low rank and sparse
- positive definite
- low rank
- linear systems
- singular values
- binary matrices
- positive semidefinite
- matrix completion
- systems of linear equations
- block diagonal
- singular vectors
- matrix multiplication
- measurement matrix
- projection matrix
- online learning
- rank minimization
- interior point methods
- eigenvalues and eigenvectors
- random projections
- prediction error
- square matrices
- real time
- sparse matrices
- convex optimization
- perturbation theory
- high dimensional
- projection matrices
- matrix representation
- sparse representation
- linear complementarity problem
- face recognition
- linear algebra
- data matrix
- covariance matrix
- least squares
- prediction model
- negative matrix factorization
- covariance matrices
- low rank matrix approximation
- missing values
- eigenvalue decomposition
- eigendecomposition
- matrix decomposition
- correlation matrix