Enhanced low-rank representation via sparse manifold adaption for semi-supervised learning

Keyphrases

• Semi-supervised Learning 100%
• Labeled Sample 10%
• Sparsity 10%
• Pattern Recognition 10%
• Data Representation 10%
• Geometric Constraints 10%
• Recognition Task 10%
• Low-rank 10%
• Classification Task 10%
• Construction Approach 10%
• Regularizer 10%
• Edge Weight 10%
• Geometrical Structure 10%
• Unlabeled Samples 10%
• Spectral Clustering 10%
• Global Information 10%
• Sparse Representation 10%
• Learning Model 10%
• Manifold Structure 10%
• Discriminative Graph 10%
• Graph Learning 10%
• Graph Construction 10%
• Ranking Data 10%

Computer Science

• Semisupervised Learning 100%
• Experimental Result 10%
• Sparsity 10%
• Data Representation 10%
• Local Information 10%
• Classification Task 10%
• Global Information 10%
• Sparse Representation 10%
• Unlabeled Sample 10%
• Spectral Clustering 10%
• Local Tangent Space 10%
• Graph Construction 10%
• Construction Approach 10%
• Supervised Classification 10%
• Pattern Recognition 10%