Robust principal component analysis via re-weighted minimization algorithms

Keyphrases

• Weight Minimization 100%
• Minimization Algorithm 100%
• Robust Principal Component Analysis 100%
• Reweighted 100%
• Efficient Implementation 33%
• Data Matrix 33%
• Sparsity Constraint 33%
• Low-dimensional Subspace 33%
• Principal Coordinate Analysis (PCoA) 33%
• Sparsity 33%
• Data Constraints 33%
• L1-norm 33%
• Linear Constraints 33%
• Linear Regression 33%
• Structural Constraints 33%
• Structural Assumption 33%
• Low-rank 33%
• Noisy Measurements 33%
• Polynomial-time Methods 33%
• Convex Problem 33%
• Error Components 33%
• Noise Component 33%
• Convergence Results 33%
• Large Rank 33%
• Nuclear Norm 33%
• High-dimensional Setting 33%
• Weighted Combination 33%
• Component Matrix 33%
• Exact Recovery 33%
• Low-rank Component 33%
• Sparse Noise 33%
• Augmented Lagrange multiplier 33%
• Majorization-minimization Algorithm 33%
• Manifold Constraint 33%
• Sparse Error 33%

Computer Science

• Component Analysis 100%
• Principal Components 100%
• Sparsity 50%
• Efficient Implementation 25%
• Data Structure 25%
• Dimensional Subspace 25%
• Data Matrix 25%
• Polynomial Time 25%
• Unknown Parameter 25%
• Linear Constraint 25%
• Lagrange Multiplier 25%
• Nuclear Norm 25%
• Structural Constraint 25%
• Recovery Requirement 25%

Engineering

• Principal Components 100%
• Component Analysis 100%
• Sparsity 50%
• Efficient Implementation 25%
• Dimensional Subspace 25%
• Matrix Component 25%
• Lagrange Multiplier Method 25%
• Convex Problem 25%
• Polynomial Time 25%
• Structural Constraint 25%
• Majorization-Minimization Algorithm 25%