K-Vectors: An Alternating Minimization Algorithm for Learning Regression Functions

Keyphrases

• Alternating Minimization 100%
• Regression Function 100%
• K-vector 100%
• K-means 80%
• Vector Algorithm 40%
• Learning Algorithm 20%
• Learnability 20%
• Support Vector Machine 20%
• Feature Space 20%
• Loss Function 20%
• Inner Product 20%
• Feature Vector 20%
• Centroid 20%
• Multi-class Classification 20%
• Mean-squared Error Distortion 20%
• Training Sequence 20%
• Squared Error Loss Function 20%
• Convex Optimization Problem 20%
• Classification Rules 20%
• Polyhedral Cells 20%
• Nearest Neighbor Rule 20%
• Response Space 20%

Mathematics

• Fixed Points 100%
• Regression Function 100%
• Nearest Neighbor 50%
• Inner Product 50%
• Loss Function 50%
• Feature Vector 50%
• Support Vector Machine 50%
• Feature Space 50%
• Centroid 50%
• Classification Rule 50%
• Training Sequence 50%
• Squared Error Loss Function 50%

Computer Science

• Regression Function 100%
• Mean Algorithm 100%
• Fixed Points 66%
• Learning Algorithm 33%
• Optimization Problem 33%
• Feature Space 33%
• Feature Vector 33%
• Support Vector Machine 33%
• Convex Optimization 33%
• Training Sequence 33%
• Multiclass Classification 33%
• Classification Rule 33%
• Polyhedral Cell 33%
• Squared Error Loss 33%