Pursuit of Low-Rank Models of Time-Varying Matrices Robust to Sparse and Measurement Noise.
Albert AkhrievJakub MarecekAndrea SimonettoPublished in: AAAI (2020)
Keyphrases
- low rank
- low rank matrix
- rank minimization
- measurement noise
- low rank subspace
- matrix completion
- low rank representation
- low rank matrices
- singular value decomposition
- robust principal component analysis
- matrix factorization
- convex optimization
- matrix decomposition
- nuclear norm
- data matrix
- low rank and sparse
- low rank approximation
- norm minimization
- sparse matrix
- linear combination
- kalman filtering
- high dimensional data
- approximation methods
- sparsity constraints
- singular values
- binary matrices
- missing data
- trace norm
- kalman filter
- high order
- pairwise
- tensor decomposition
- signal recovery
- collaborative filtering