A Nonconvex Relaxation Approach to Low-Rank Tensor Completion.
Xiongjun ZhangPublished in: IEEE Trans. Neural Networks Learn. Syst. (2019)
Keyphrases
- low rank
- convex optimization
- trace norm
- convex relaxation
- frobenius norm
- low rank matrices
- tensor decomposition
- high order
- robust principal component analysis
- low rank matrix recovery
- matrix completion
- objective function
- low rank matrix
- matrix factorization
- rank minimization
- low rank and sparse
- kernel matrix
- higher order
- linear combination
- missing data
- matrix decomposition
- high dimensional data
- semi supervised
- singular value decomposition
- interior point methods
- total variation
- primal dual
- tensor factorization
- singular values
- dimensionality reduction
- pairwise
- nuclear norm
- data matrix
- pattern recognition
- minimization problems
- reconstruction error
- feature extraction
- image processing
- collaborative filtering
- norm minimization
- iterative algorithms
- machine learning