Low-Rank PSD Approximation in Input-Sparsity Time.
Kenneth L. ClarksonDavid P. WoodruffPublished in: SODA (2017)
Keyphrases
- low rank
- sparsity constraints
- matrix decomposition
- linear combination
- low rank matrix
- missing data
- matrix factorization
- sparse approximation
- convex optimization
- matrix completion
- rank minimization
- low rank approximation
- singular value decomposition
- high dimensional data
- semi supervised
- approximation methods
- kernel matrix
- trace norm
- high order
- minimization problems
- singular values
- low rank matrices
- regularized regression
- nonnegative matrix factorization
- tensor factorization
- learning algorithm
- feature selection
- data matrix
- input data
- active learning
- pairwise
- non rigid structure from motion
- pattern recognition