Universality laws for randomized dimension reduction, with applications.
Samet OymakJoel A. TroppPublished in: CoRR (2015)
Keyphrases
- dimension reduction
- feature extraction
- principal component analysis
- feature selection
- high dimensional data
- high dimensional
- high dimensional problems
- low dimensional
- high dimensionality
- singular value decomposition
- variable selection
- random projections
- data mining and machine learning
- feature space
- partial least squares
- dimensionality reduction
- linear discriminant analysis
- dimension reduction methods
- high dimensional data analysis
- unsupervised learning
- cluster analysis
- discriminative information
- intrinsic dimension
- manifold learning
- probabilistic model
- object recognition
- decision trees
- neural network