Multifidelity Dimension Reduction via Active Subspaces.
Rémi R. LamOlivier ZahmYoussef M. MarzoukKaren E. WillcoxPublished in: SIAM J. Sci. Comput. (2020)
Keyphrases
- dimension reduction
- high dimensional data
- principal component analysis
- low dimensional
- high dimensional
- linear projection
- feature space
- feature subspace
- high dimensionality
- variable selection
- dimensionality reduction
- data mining and machine learning
- feature extraction
- high dimensional problems
- discriminative information
- partial least squares
- feature selection
- manifold learning
- linear discriminant analysis
- nearest neighbor
- random projections
- high dimensional data analysis
- lower dimensional
- singular value decomposition
- preprocessing
- data points
- original data
- unsupervised learning
- machine learning
- cluster analysis
- subspace clustering
- data sets
- linear subspace
- maximum likelihood
- semi supervised
- feature vectors
- computer vision