A Low-Rank Approach to Off-The-Grid Sparse Deconvolution.
Paul CatalaVincent DuvalGabriel PeyréPublished in: CoRR (2017)
Keyphrases
- low rank
- low rank matrix
- rank minimization
- low rank subspace
- low rank matrices
- sparsity constraints
- nuclear norm
- sparse linear
- robust principal component analysis
- low rank representation
- group sparsity
- matrix factorization
- missing data
- convex optimization
- kernel matrices
- linear combination
- singular value decomposition
- matrix decomposition
- least squares
- regularized regression
- matrix completion
- semi supervised
- kernel matrix
- low rank approximation
- high order
- high dimensional data
- tensor decomposition
- data sets
- singular values
- minimization problems
- data matrix
- sparse coding
- image restoration
- sparse matrix
- feature extraction
- machine learning
- high dimensional
- learning algorithm
- face recognition
- sparse representation
- natural images
- small number
- pairwise