The Sparse Reverse of Principal Component Analysis for Fast Low-Rank Matrix Completion.
Abdallah A. ChehadeZunya ShiPublished in: CoRR (2019)
Keyphrases
- matrix completion
- low rank
- principal component analysis
- singular value decomposition
- low rank matrices
- rank minimization
- low rank matrix
- norm regularization
- nuclear norm
- matrix factorization
- dimensionality reduction
- linear combination
- missing data
- low rank approximation
- convex optimization
- high dimensional data
- singular values
- kernel matrix
- principal components
- norm minimization
- random projections
- tensor decomposition
- semi supervised
- low dimensional
- high order
- sparse representation
- high dimensional
- negative matrix factorization
- data matrix
- least squares
- trace norm
- minimization problems
- affinity matrix
- higher order
- feature extraction
- face recognition
- small number
- collaborative filtering
- learning algorithm