Dimensionality reduction of SDPs through sketching.
Andreas BluhmDaniel Stilck FrançaPublished in: CoRR (2017)
Keyphrases
- dimensionality reduction
- high dimensional
- data representation
- high dimensionality
- principal component analysis
- low dimensional
- high dimensional data
- feature extraction
- linear dimensionality reduction
- structure preserving
- pattern recognition
- linear projection
- manifold learning
- input space
- principal components
- dimension reduction
- nonlinear dimensionality reduction
- kernel pca
- data points
- dimensionality reduction methods
- kernel learning
- linear discriminant analysis
- lower dimensional
- random projections
- diffusion maps
- euclidean distance
- feature selection
- supervised dimensionality reduction
- sketch recognition
- pattern recognition and machine learning
- graph embedding
- metric learning
- singular value decomposition
- feature space
- knowledge base
- genetic algorithm
- principal components analysis
- neural network