Probabilistic Learning Vector Quantization on Manifold of Symmetric Positive Definite Matrices.
Fengzhen TangHaifeng FengPeter TiñoBailu SiDaxiong JiPublished in: CoRR (2021)
Keyphrases
- learning vector quantization
- symmetric positive definite matrices
- dictionary learning
- valued data
- matrix valued
- riemannian manifolds
- vector space
- sparse coding
- riemannian metric
- self organizing maps
- sparse representation
- neural network
- bayesian networks
- euclidean space
- dt mri
- feature space
- image representation
- probabilistic model
- computer vision
- infinite dimensional
- image classification
- low dimensional
- magnetic resonance images
- manifold learning
- parameter space
- unsupervised learning