A Relaxed Interior Point Method for Low-Rank Semidefinite Programming Problems with Applications to Matrix Completion.
Stefania BellaviaJacek GondzioMargherita PorcelliPublished in: J. Sci. Comput. (2021)
Keyphrases
- low rank
- semidefinite programming
- matrix completion
- kernel matrix
- interior point methods
- convex optimization
- trace norm
- missing data
- primal dual
- matrix factorization
- linear combination
- semi supervised
- linear programming
- singular value decomposition
- convex relaxation
- high dimensional data
- singular values
- solving problems
- image processing
- missing values
- high order
- low dimensional
- collaborative filtering
- learning algorithm
- total variation
- linear program
- incomplete data
- maximum likelihood
- higher order
- recommender systems
- data analysis
- training data