Manifold learning for parameter reduction.
Alexander HolidayMahdi KooshkbaghiJuan M. Bello-RivasC. William GearAntonios ZagarisIoannis G. KevrekidisPublished in: J. Comput. Phys. (2019)
Keyphrases
- manifold learning
- low dimensional
- dimensionality reduction
- nonlinear dimensionality reduction
- semi supervised
- dimension reduction
- high dimensional
- laplacian eigenmaps
- manifold learning algorithm
- high dimensional data
- feature extraction
- diffusion maps
- head pose estimation
- subspace learning
- locality preserving
- feature space
- manifold structure
- locally linear embedding
- discriminant projection
- data mining
- geodesic distance
- sparse representation
- parameter space
- linear discriminant analysis
- image classification
- feature vectors
- pattern recognition
- learning algorithm
- neural network