Completion of structurally-incomplete matrices with reweighted low-rank and sparsity priors.
Jing-Yu YangXuemeng YangXinchen YePublished in: ICASSP (2016)
Keyphrases
- low rank
- missing data
- sparsity constraints
- matrix completion
- low rank matrix
- singular value decomposition
- data matrix
- singular values
- frobenius norm
- matrix decomposition
- matrix factorization
- missing values
- low rank approximation
- eigendecomposition
- low rank and sparse
- linear combination
- convex optimization
- affinity matrix
- high dimensional data
- low rank matrices
- regularized regression
- kernel matrix
- rank minimization
- measurement matrix
- high dimensional
- tensor factorization
- semi supervised
- incomplete data
- sparse representation
- high order
- least squares
- binary matrix
- feature extraction
- robust principal component analysis
- recommender systems
- trace norm
- norm minimization
- total variation