Reconstruction of Structurally-Incomplete Matrices With Reweighted Low-Rank and Sparsity Priors.
Jing-Yu YangXuemeng YangXinchen YeChunping HouPublished in: IEEE Trans. Image Process. (2017)
Keyphrases
- low rank
- sparsity constraints
- missing data
- matrix completion
- low rank matrix
- singular value decomposition
- data matrix
- singular values
- frobenius norm
- matrix decomposition
- eigendecomposition
- low rank approximation
- reconstruction error
- low rank and sparse
- linear combination
- convex optimization
- matrix factorization
- affinity matrix
- rank minimization
- low rank matrices
- measurement matrix
- kernel matrix
- missing values
- non rigid structure from motion
- incomplete data
- semi supervised
- high dimensional data
- trace norm
- data sets
- high order
- image reconstruction
- binary matrices
- structure from motion
- regularized regression
- similarity measure
- binary matrix
- discrete tomography
- compressive sensing
- sparse representation
- input data
- small number
- high dimensional