A regularized point-to-manifold distance metric for multi-view multi-manifold learning.
Faraein AeiniAmir-Masoud Eftekhari-MoghadamPublished in: Eng. Appl. Artif. Intell. (2019)
Keyphrases
- manifold learning
- multi view
- distance metric
- semi supervised
- metric learning
- low dimensional
- data points
- nonlinear dimensionality reduction
- dimensionality reduction
- euclidean distance
- multiple views
- geodesic distance
- laplacian eigenmaps
- high dimensional data
- high dimensional
- d objects
- semi supervised learning
- distance measure
- dimension reduction
- feature extraction
- three dimensional
- distance function
- euclidean space
- least squares
- statistical learning
- labeled data
- neural network
- supervised learning
- sparse representation
- principal component analysis
- unsupervised learning
- low rank
- nearest neighbor
- pairwise
- gaussian process
- feature space
- riemannian manifolds
- locally linear embedding
- support vector
- image processing