Entropy-Isomap: Manifold Learning for High-dimensional Dynamic Processes.
Frank SchoenemanVarun ChandolaNils NappOlga WodoJaroslaw ZolaPublished in: IEEE BigData (2018)
Keyphrases
- manifold learning
- high dimensional
- low dimensional
- dimensionality reduction
- nonlinear dimensionality reduction
- dimension reduction
- locally linear embedding
- semi supervised
- high dimensional data
- diffusion maps
- feature mapping
- subspace learning
- laplacian eigenmaps
- manifold learning algorithm
- feature space
- nonlinear dimension reduction
- data points
- neighborhood graph
- low dimensional manifolds
- geodesic distance
- high dimensionality
- feature extraction
- manifold structure
- neural network
- embedding space
- lower dimensional
- principal component analysis
- learning algorithm