Subspace Sequentially Iterative Leaning for Semi-Supervised SVM

Keyphrases

• Classification Performance 33%
• Classifier Learning 33%
• Data Classifier 33%
• Data Issues 33%
• Difficult Problem 33%
• Dimensionality Reduction 33%
• Dual Problem 33%
• Effective Mechanism 33%
• Graph Laplacian 33%
• Graph Regularization 33%
• High-dimensional Data 66%
• Incremental Support Vector Machine 33%
• Joint Sparsity 33%
• Karush-Kuhn-Tucker Conditions 33%
• Large Margin 33%
• Large-scale Data 33%
• Optimal Classification 33%
• Optimal Subspaces 33%
• Original Problem 33%
• Partially Labeled 33%
• Process Optimization 33%
• Regression Learning 33%
• Semi-supervised Framework 33%
• Semi-supervised Learning 33%
• Semi-supervised Support Vector Machine 100%
• Subspace Learning 33%
• Support Vector Learning 33%
• Support Vector Machine Classifier 33%
• Unified Framework 33%

Computer Science

• Classification Performance 25%
• Data Processing 25%
• Dimensionality Reduction 25%
• Dual Problem 25%
• Extracted Feature 25%
• High Dimensional Data 50%
• Joint Sparsity 25%
• Laplace Operator 25%
• Large Scale Data 25%
• Process Optimization 25%
• Regularization 25%
• Semisupervised Learning 25%
• Support Vector 25%
• Support Vector Machine 100%
• Support Vector Machine 50%
• Unified Framework 25%