A fast neural network learning algorithm with approximate singular value decomposition - Jankowski, Norbert; Linowiecki, Rafał (Zielona Góra: Uniwersytet Zielonogórski)
The learning of neural networks is becoming more and more important. Researchers have constructed dozens of learning algorithms, but it is still necessary to develop faster, more flexible, or more accurate learning algorithms. With fast learning we can examine more learning scenarios for a given problem, especially in the case of meta-learning. In this article we focus on the construction of a much faster learning algorithm and its modifications, especially for nonlinear versions of neural networks.
Keywords: Moore?Penrose pseudo-inverse learning; radial basis function network; extreme learning machines; kernel methods; machine learning; Singular Value Decomposition (SVD); deep extreme learning; principal component analysis (PCA)