A scalable projective scaling algorithm for l_p loss with convex penalizations

Keyphrases

• Lp Loss 100%
• Scaling Algorithm 100%
• Penalization 100%
• Message-passing Algorithms 100%
• Learning Algorithm 33%
• Matrix Inversion 33%
• Face Image 33%
• Globally Convergent 33%
• Inversion Method 33%
• Stationary Point 33%
• Loss Function 33%
• Image Classification 33%
• Accurate Algorithm 33%
• Equivalent Problems 33%
• Convex Function 33%
• Scaling Conditions 33%
• Problem Size 33%
• Overcomplete Dictionary Learning 33%
• Scalable Algorithms 33%
• Nonconvex 33%
• Linear Scalability 33%
• Additive Components 33%
• Second-order Learning 33%
• Sparse Signal Recovery 33%
• Penalization Method 33%
• Matrix-vector multiplication 33%
• Convex Formulation 33%
• Learning Procedure 33%

Computer Science

• Message Passing 100%
• Efficient Algorithm 33%
• Learning Algorithm 33%
• Image Classification 33%
• Vector Multiplication 33%
• Stationary Point 33%
• Dictionary Learning 33%
• Convex Function 33%
• Learning Problem 33%
• Additive Component 33%

Mathematics

• Projective 100%
• Loss Function 50%
• Matrix Inversion 50%
• Stationary Point 50%
• Convex Function 50%
• Matrix-Vector Multiplication 50%