Tensor Robust Principal Component Analysis: Exact Recovery of Corrupted Low-Rank Tensors via Convex Optimization.
Canyi LuJiashi FengYudong ChenWei LiuZhouchen LinShuicheng YanPublished in: CoRR (2017)
Keyphrases
- low rank
- robust principal component analysis
- convex optimization
- low rank matrix recovery
- high order
- trace norm
- low rank and sparse
- low rank matrix
- matrix completion
- higher order
- rank minimization
- interior point methods
- kernel matrix
- total variation
- convex relaxation
- norm minimization
- primal dual
- minimization problems
- nuclear norm
- pairwise
- markov random field
- image denoising
- denoising
- small number
- multiscale
- computer vision
- singular values
- learning problems
- data matrix
- learning tasks
- dimensionality reduction