A parallel primal-dual interior-point method for semidefinite programs using positive definite matrix completion.
Kazuhide NakataMakoto YamashitaKatsuki FujisawaMasakazu KojimaPublished in: Parallel Comput. (2006)
Keyphrases
- interior point methods
- semidefinite
- primal dual
- semidefinite programming
- convex optimization
- low rank
- kernel matrix
- linear programming
- linear program
- approximation algorithms
- convergence rate
- quadratic programming
- kernel function
- total variation
- solving problems
- machine learning
- convex relaxation
- matrix factorization
- singular value decomposition
- linear combination
- training data
- learning algorithm