Scalable conditional deep inverse Rosenblatt transports using tensor trains and gradient-based dimension reduction.
Tiangang CuiSergey DolgovOlivier ZahmPublished in: J. Comput. Phys. (2023)
Keyphrases
- dimension reduction
- dimensionality reduction
- feature extraction
- principal component analysis
- matrix inversion
- high dimensional problems
- high dimensional
- low dimensional
- singular value decomposition
- high dimensionality
- high dimensional data
- feature selection
- manifold learning
- data mining and machine learning
- feature space
- variable selection
- random projections
- unsupervised learning
- linear discriminant analysis
- cluster analysis
- least squares
- preprocessing
- discriminative information
- dimension reduction methods
- high dimensional data analysis
- partial least squares
- computer vision
- face recognition
- data mining