Low-Rank Riemannian Optimization on Positive Semidefinite Stochastic Matrices with Applications to Graph Clustering.
Ahmed DouikBabak HassibiPublished in: ICML (2018)
Keyphrases
- low rank
- positive semidefinite
- graph clustering
- kernel matrix
- linear combination
- convex optimization
- matrix factorization
- singular value decomposition
- low rank matrix
- missing data
- high dimensional data
- semidefinite programming
- semi supervised
- high order
- weighted graph
- semidefinite
- kernel function
- clustering method
- manifold learning
- total variation
- reproducing kernel hilbert space
- data sets
- kernel methods
- small number
- face recognition