Low-Rank Toeplitz Matrix Estimation Via Random Ultra-Sparse Rulers.
Hannah LawrenceJerry LiCameron MuscoChristopher MuscoPublished in: ICASSP (2020)
Keyphrases
- low rank
- regularized regression
- low rank matrix
- rank minimization
- nuclear norm
- low rank matrices
- low rank subspace
- linear combination
- convex optimization
- singular value decomposition
- matrix decomposition
- matrix factorization
- matrix completion
- missing data
- robust principal component analysis
- sparsity constraints
- kernel matrices
- low rank approximation
- low rank representation
- kernel matrix
- high order
- least squares
- semi supervised
- trace norm
- low rank and sparse
- high dimensional data
- tensor decomposition
- singular values
- frobenius norm
- factorization methods
- data matrix
- minimization problems
- sparse matrix
- affinity matrix
- missing values
- dimensionality reduction
- norm minimization
- data sets
- sparse representation
- recommender systems
- high dimensional