Fast and Robust Spectrally Sparse Signal Recovery: A Provable Non-Convex Approach via Robust Low-Rank Hankel Matrix Reconstruction.
HanQin CaiJian-Feng CaiTianming WangGuojian YinPublished in: CoRR (2019)
Keyphrases
- low rank
- rank minimization
- low rank matrix
- nuclear norm
- low rank subspace
- convex optimization
- signal recovery
- low rank representation
- low rank and sparse
- robust principal component analysis
- low rank matrices
- matrix completion
- matrix factorization
- singular value decomposition
- missing data
- linear combination
- semi supervised
- sparse matrix
- low rank approximation
- compressed sensing
- singular values
- data sets