Diffusion Maps for Signal Processing: A Deeper Look at Manifold-Learning Techniques Based on Kernels and Graphs.
Ronen TalmonIsrael CohenSharon GannotRonald R. CoifmanPublished in: IEEE Signal Process. Mag. (2013)
Keyphrases
- diffusion maps
- manifold learning
- signal processing
- nonlinear dimensionality reduction
- sparse representation
- low dimensional
- dimensionality reduction
- feature space
- pattern recognition
- image processing
- high dimensional
- semi supervised
- subspace learning
- dimension reduction
- high dimensional data
- riemannian manifolds
- feature extraction
- kernel function
- neural network
- geodesic distance
- locally linear embedding
- data sets
- input space
- statistical learning
- image classification
- principal component analysis
- manifold structure
- data analysis