Solving nonlinear svm in linear time? A nyström zpproximated svm with applications to image classification^∗

Keyphrases

• Linear Time 100%
• Image Classification 100%
• Linear SVM 66%
• Selection Strategy 33%
• Computation Time 33%
• Decomposition Method 33%
• Performance Guarantee 33%
• Support Vector Machine 33%
• Recognition Performance 33%
• Computation Complexity 33%
• Image Data 33%
• Data Representation 33%
• Base Matrix 33%
• Matrix Selection 33%
• Data Matrix 33%
• Nonlinear SVM 33%
• Instance Selection 33%
• Nystrm Approximation 33%

Computer Science

• Support Vector Machine 100%
• Image Classification 100%
• Svm 100%
• Approximation (Algorithm) 50%
• Recognition Performance 25%
• Computation Complexity 25%
• Computation Time 25%
• Data Representation 25%
• Performance Guarantee 25%
• Data Matrix 25%
• Instance Selection 25%
• Selection Matrix 25%