Covariance matrix testing in high dimension using random projections.
Deepak Nag AyyalaSantu GhoshDaniel F. LinderPublished in: Comput. Stat. (2022)
Keyphrases
- covariance matrix
- random projections
- high dimension
- principal component analysis
- dimensionality reduction
- feature space
- low dimensional
- sample size
- small sample
- covariance matrices
- high dimensional data
- random sampling
- dimension reduction
- high dimensional
- input space
- real valued
- feature selection
- sparse representation
- original data
- high dimensionality
- support vector machine
- linear discriminant analysis
- objective function
- image reconstruction
- data sets
- machine learning
- unsupervised learning
- hash functions
- pattern recognition
- model selection
- feature extraction
- decision trees
- nearest neighbor