Low-Rank Sparse Tensor Approximations for Large High-Resolution Videos.
Xiang LiuHuyunting HuangWeitao TangTonglin ZhangBaijian YangPublished in: ICMLA (2020)
Keyphrases
- low rank
- tensor decomposition
- high resolution
- high order
- trace norm
- low rank matrix
- low rank matrices
- rank minimization
- frobenius norm
- low rank subspace
- matrix factorization
- low resolution
- missing data
- nuclear norm
- linear combination
- tensor factorization
- super resolution
- convex optimization
- matrix completion
- low rank representation
- singular value decomposition
- kernel matrix
- semi supervised
- kernel matrices
- robust principal component analysis
- matrix decomposition
- low rank approximation
- high dimensional data
- video sequences
- regularized regression
- image processing
- high quality
- sparse coding
- compressive sensing
- minimization problems
- singular values
- higher order
- approximation methods
- data matrix
- video surveillance
- sparse representation
- pattern recognition
- auxiliary information
- affinity matrix
- random projections
- image sequences