Low-rank Sparse Decomposition of Graph Adjacency Matrices for Extracting Clean Clusters.
Taiju KanadaMasaki OnukiYuichi TanakaPublished in: APSIPA (2018)
Keyphrases
- low rank
- low rank and sparse
- low rank matrix
- tensor decomposition
- low rank matrices
- robust principal component analysis
- signal recovery
- matrix completion
- rank minimization
- low rank approximation
- singular value decomposition
- convex optimization
- linear combination
- low rank subspace
- missing data
- affinity matrix
- matrix decomposition
- matrix factorization
- nuclear norm
- graph clustering
- low rank representation
- data matrix
- semi supervised
- clustering algorithm
- singular values
- kernel matrix
- sparsity constraints
- high order
- high dimensional data
- frobenius norm
- eigendecomposition
- adjacency matrix
- graph matching
- binary matrices
- weighted graph
- regularized regression
- sparse matrix
- pairwise
- face recognition
- least squares
- markov random field
- data clustering
- sparse coding
- normalized cut
- rows and columns