联合低秩和p稀疏约束矩阵回归的人脸识别算法 (Face Recognition Based on Matrix Regression with Low-rank and p Sparse Constraints).
Guoliang YangLu LuoHairong LuYiqin FengLiming LiangPublished in: 计算机科学 (2015)
Keyphrases
- low rank
- sparse regression
- low rank matrix
- rank minimization
- face recognition
- nuclear norm
- low rank matrices
- low rank subspace
- singular value decomposition
- regularized regression
- matrix decomposition
- linear combination
- convex optimization
- matrix factorization
- missing data
- robust principal component analysis
- matrix completion
- low rank representation
- kernel matrices
- sparsity constraints
- kernel matrix
- high order
- low rank approximation
- trace norm
- high dimensional data
- low rank and sparse
- semi supervised
- factorization methods
- singular values
- frobenius norm
- data matrix
- principal component analysis
- tensor decomposition
- affinity matrix
- robust face recognition
- sparse representation
- minimization problems
- least squares
- computer vision
- compressive sensing
- subspace learning
- random projections
- face images
- pairwise
- image processing