Greedy construction of quadratic manifolds for nonlinear dimensionality reduction and nonlinear model reduction.
Paul SchwerdtnerBenjamin PeherstorferPublished in: CoRR (2024)
Keyphrases
- nonlinear dimensionality reduction
- nonlinear models
- manifold learning
- laplacian eigenmaps
- low dimensional
- dimensionality reduction
- linear model
- high dimensional data
- riemannian manifolds
- low dimensional manifolds
- locally linear embedding
- linear models
- statistical models
- high dimensional
- dimension reduction
- dimensionality reduction methods
- data mining
- feature extraction
- control law
- data sets
- pairwise
- pattern recognition
- feature selection
- active learning
- computer vision
- dynamic programming
- least squares