Statistically Guided Divide-and-Conquer for Sparse Factorization of Large Matrix.
Kun ChenRuipeng DongWanwan XuZemin ZhengPublished in: CoRR (2020)
Keyphrases
- tensor factorization
- missing entries
- low rank
- factorization methods
- singular value decomposition
- low rank matrix
- matrix factorization
- matrix completion
- factorization method
- tensor decomposition
- low rank matrices
- coefficient matrix
- measurement matrix
- rank minimization
- sparse matrices
- data matrix
- sparse matrix
- convex optimization
- singular vectors
- random projections
- linear algebra
- singular values
- collaborative filtering
- low rank approximation
- sparse data
- negative matrix factorization
- linear combination
- sparsity constraints
- kernel matrices
- nonnegative matrix factorization
- original data
- positive semi definite
- rows and columns
- non rigid structure from motion
- signal recovery
- low rank and sparse
- condition number
- neural network
- compressed sensing
- gaussian processes
- structure from motion
- sparse representation
- high dimensional
- pairwise