Dimension reduction for semidefinite programs via Jordan algebras.
Frank PermenterPablo A. ParriloPublished in: Math. Program. (2020)
Keyphrases
- dimension reduction
- semidefinite
- semidefinite programming
- principal component analysis
- feature extraction
- high dimensional
- low dimensional
- higher dimensional
- feature selection
- singular value decomposition
- convex relaxation
- high dimensional data
- variable selection
- linear discriminant analysis
- cluster analysis
- sufficient conditions
- manifold learning
- interior point methods
- convex sets
- feature space
- data sets
- dimensionality reduction
- finite dimensional
- unsupervised learning
- linear programming
- convex optimization
- data points
- reinforcement learning
- computer vision
- machine learning
- data mining