Low-Rank Riemannian Optimization for Graph-Based Clustering Applications.
Ahmed DouikBabak HassibiPublished in: IEEE Trans. Pattern Anal. Mach. Intell. (2022)
Keyphrases
- low rank
- high dimensional data
- semi supervised
- nuclear norm
- convex optimization
- matrix factorization
- missing data
- singular value decomposition
- rank minimization
- low rank matrix
- linear combination
- matrix completion
- clustering method
- matrix decomposition
- clustering algorithm
- document clustering
- kernel matrix
- high order
- data clustering
- manifold learning
- k means
- low rank matrices
- convex relaxation
- data matrix
- minimization problems
- unsupervised learning
- data sets
- robust principal component analysis
- least squares
- affinity matrix
- singular values
- nonnegative matrix factorization
- euclidean space