Matrix Normal PCA for Interpretable Dimension Reduction and Graphical Noise Modeling.
Chihao ZhangKuo GaiShihua ZhangPublished in: CoRR (2019)
Keyphrases
- dimension reduction
- principal component analysis
- singular value decomposition
- principle component analysis
- qr decomposition
- high dimensional
- feature extraction
- random projections
- dimension reduction methods
- covariance matrix
- dimensionality reduction
- high dimensional problems
- linear discriminant analysis
- high dimensional data
- low dimensional
- singular values
- feature space
- manifold learning
- partial least squares
- face recognition
- least squares
- independent component analysis
- principal components
- discriminative information
- unsupervised learning
- cluster analysis
- high dimensionality
- preprocessing
- feature selection
- neural network
- high dimensional data analysis
- principal components analysis
- lower dimensional
- discriminant analysis
- optical flow
- decision trees
- computer vision