Kernel Clustering On Symmetric Positive Definite Manifolds Via Double Approximated Low Rank Representation.
Xinglin PiaoYongli HuJunbin GaoYanfeng SunXin YangBaocai YinWenwu ZhuGe LiPublished in: ICME (2020)
Keyphrases
- riemannian manifolds
- symmetric positive definite
- positive definite
- low rank representation
- kernel matrix
- low rank
- clustering algorithm
- affinity matrix
- clustering method
- spectral clustering
- high dimensional data
- euclidean space
- k means
- kernel function
- feature space
- geometric structure
- data clustering
- support vector
- manifold learning
- linear combination
- vector space
- kernel methods
- covariance matrix
- subspace clustering
- unsupervised learning
- low dimensional
- support vector machine
- knn