Multi-kernel sparse subspace clustering on the Riemannian manifold of symmetric positive definite matrices.
Sabra HechmiAbir GallasEzzeddine ZagroubaPublished in: Pattern Recognit. Lett. (2019)
Keyphrases
- riemannian manifolds
- euclidean space
- high dimensional data
- high dimensional
- manifold learning
- parameter space
- sparse representation
- mean shift
- vector space
- multi class classification
- geometric structure
- feature space
- data points
- geodesic distance
- low dimensional
- covariance matrices
- clustering method
- sparse coding
- dimensionality reduction
- clustering algorithm
- multi class
- reproducing kernel hilbert space
- euclidean distance
- similarity search
- covariance matrix
- learning problems
- high dimensionality
- learning theory