Generalized Embedding Regression: A Framework for Supervised Feature Extraction

Keyphrases

• Supervised Feature Extraction 100%
• Jointly Sparse 100%
• Sparse Embedding 83%
• Orthogonal Constraint 33%
• Penalty Graph 33%
• Sparse Representation Learning 33%
• Optimization Problem 16%
• Regularization Term 16%
• Recognition Task 16%
• L1-norm 16%
• Label Information 16%
• Performance Properties 16%
• Approximate Solution 16%
• Feature Extraction Methods 16%
• Competitive Performance 16%
• Data Variability 16%
• Projection Learning 16%
• Inter-class Separability 16%
• Correlation Structure 16%
• Iterative Algorithm 16%
• Regression Matrix 16%
• Semantic Interpretability 16%
• Constraint Matrix 16%
• Latent Properties 16%
• Rank Constraint 16%
• Intrinsic Graphs 16%
• Robustness to Outliers 16%
• Low-dimensional Embedding 16%
• Procrustes Problem 16%
• Graph Laplacian 16%
• Inter-class Similarity 16%
• Discriminative Projection 16%

Computer Science

• Feature Extraction 100%
• Experimental Result 50%
• Interpretability 50%
• Good Performance 50%
• Regularization Term 50%
• Optimization Problem 50%
• Objective Function 50%
• Laplace Operator 50%
• Approximate Solution 50%
• Iterative Algorithm 50%