On Low Rank Matrix Approximations with Applications to Synthesis Problem in Compressed Sensing.
Anatoli B. JuditskyFatma Kilinç-KarzanArkadi NemirovskiPublished in: SIAM J. Matrix Anal. Appl. (2011)
Keyphrases
- compressed sensing
- low rank matrix
- approximation methods
- low rank
- image reconstruction
- random projections
- sparse matrix
- singular value decomposition
- convex optimization
- matrix factorization
- sparse representation
- natural images
- signal processing
- orthogonal matching pursuit
- compressive sensing
- fourier domain
- image processing
- radon transform
- linear combination
- semi supervised
- object recognition
- data sets
- high order
- document collections
- motion estimation
- similarity measure
- signal recovery