Lie PCA: Density estimation for symmetric manifolds.
Jameson CahillDustin G. MixonHans ParshallPublished in: CoRR (2020)
Keyphrases
- density estimation
- principal component analysis
- low dimensional
- mixture model
- probability density function
- high dimensional
- feature space
- dimensionality reduction
- mixture modeling
- manifold learning
- probability density
- outlier detection
- nonparametric density estimation
- principal components
- euclidean space
- face recognition
- density function
- kernel pca
- gaussian mixture model
- parzen window
- density estimators
- feature extraction
- multivariate gaussian distribution
- kernel density estimation
- density estimates
- dimension reduction
- covariance matrix
- em algorithm
- expectation maximization
- data mining
- subspace methods
- maximum likelihood
- probabilistic model
- machine learning