A Sherman-Morrison-Woodbury approach to solving least squares problems with low-rank updates.
Stefan GüttelYuji NakatsukasaMarcus WebbAlban Bloor RileyPublished in: CoRR (2024)
Keyphrases
- low rank
- least squares
- matrix completion
- sparse linear
- solving problems
- missing data
- singular value decomposition
- linear combination
- rank minimization
- matrix factorization
- machine learning
- kernel matrix
- low rank matrix
- robust principal component analysis
- matrix decomposition
- nonnegative matrix factorization
- high order
- high dimensional data
- semi supervised
- similarity measure