Entropy-Isomap: Manifold Learning for High-dimensional Dynamic Processes.
Frank SchoenemanVarun ChandolaNils NappOlga WodoJaroslaw ZolaPublished in: CoRR (2018)
Keyphrases
- manifold learning
- high dimensional
- low dimensional
- dimensionality reduction
- nonlinear dimensionality reduction
- high dimensional data
- dimension reduction
- manifold learning algorithm
- semi supervised
- diffusion maps
- laplacian eigenmaps
- subspace learning
- locally linear embedding
- low dimensional manifolds
- feature extraction
- feature mapping
- high dimensionality
- nonlinear dimension reduction
- neighborhood graph
- similarity search
- feature selection
- geodesic distance
- principal component analysis
- nearest neighbor
- data points
- metric space
- least squares
- input space
- lower dimensional
- dimensional data
- noisy data
- manifold structure
- discriminant analysis
- multi dimensional
- feature vectors
- neural network