Small populations, high-dimensional spaces: Sparse covariance matrix adaptation.
Silja Meyer-NiebergErik KropatPublished in: FedCSIS (2015)
Keyphrases
- covariance matrix
- high dimensional spaces
- high dimensional
- nearest neighbor
- covariance matrices
- principal component analysis
- high dimensional data
- dimensionality reduction
- low dimensional
- euclidean distance
- sample size
- gaussian mixture
- eigendecomposition
- symmetric matrix
- correlation matrix
- eigenvalues and eigenvectors
- geometrical interpretation
- high dimensionality
- dimensional data
- class conditional densities
- data sets
- data points
- sparse representation
- model selection
- maximum likelihood
- evolutionary algorithm
- training set
- search algorithm
- cma es
- learning algorithm