Discover latent discriminant information for dimensionality reduction: Non-negative sparseness preserving embedding

Keyphrases

• Dimensionality Reduction 100%
• Discriminant Information 100%
• Sparsity Preserving Projection 100%
• Locality Preserving Projection 66%
• Sparse Representation 66%
• Non-negative Sparse Representation 66%
• Feature Extraction 33%
• State-of-the-art Techniques 33%
• Information Processing 33%
• Projection Algorithm 33%
• Weight Matrix 33%
• Primates 33%
• Linear Dimensionality Reduction 33%
• Learning-based 33%
• Low-dimensional Subspace 33%
• Comprehensive Comparison 33%
• Competitive Performance 33%
• Manifold Learning Algorithm 33%
• Visual Cortex 33%
• Discriminant Ability 33%
• Neuron Cells 33%
• Manifold Learning 33%
• Sparse Reconstruction 33%
• Representation Coefficients 33%
• Training Step 33%
• Unsupervised Learning Algorithm 33%
• Subspace Learning 33%
• Unsupervised Learning Techniques 33%
• Active Neuron 33%
• Sparseness Constraint 33%

Computer Science

• Dimensionality Reduction 100%
• Sparse Representation 100%
• Sparsity 75%
• Unsupervised Learning 50%
• locality preserving projection 50%
• Learning Algorithm 50%
• Manifold Learning 50%
• Information Processing 25%
• Dimensional Subspace 25%
• Feature Extraction 25%