Kernel Sparse Subspace Clustering on Symmetric Positive Definite Manifolds.

Ming Yin Yi Guo Junbin Gao Zhaoshui He Shengli Xie

Published in: CoRR (2016)

Keyphrases

subspace clustering
riemannian manifolds
high dimensional
symmetric positive definite
positive definite
high dimensional data
kernel function
feature space
manifold learning
euclidean space
kernel matrix
low dimensional

subspace clusters
geometric structure
reproducing kernel hilbert space
input space
parameter space
high dimensionality
clustering method
sparse representation
kernel methods
clustering algorithm
dimensionality reduction
similarity search

covariance matrix
distribution function
data points
dimension reduction
low rank
text data
vector space
lie group
higher dimensional
mean shift
nearest neighbor
image processing

geodesic distance
kernel pca
kernel machines
principal component analysis
feature extraction
support vector
support vector machine
diffusion tensor
gaussian processes
data sets
shape analysis