Low-complexity subspace-descent over symmetric positive definite manifold.
Yogesh DarmwalKetan RajawatPublished in: CoRR (2023)
Keyphrases
- low complexity
- symmetric positive definite
- spd matrices
- riemannian manifolds
- distribution function
- low dimensional
- positive definite
- diffusion tensor
- computational complexity
- linear subspace
- feature space
- principal component analysis
- euclidean space
- von neumann
- high dimensional data
- lie group
- motion estimation
- covariance matrices
- manifold learning
- high dimensional
- feature extraction
- dimensionality reduction
- computer vision
- kernel matrix
- covariance matrix
- vector space
- video coding
- data points
- feature vectors
- face recognition
- machine learning