Neural Network Learning: Theoretical Foundations

Machine learning, and more particularly learning with neural networks, can be viewed as just such a phenomenon. Frequently remarkable performance is obtained by training networks to perform relatively complex AI tasks. The need for a fuller theoretical analysis and understanding of their performance has been a major research objective for the last decade. Neural Network Learning: Theoretical Foundations reports on important developments that have been made toward this goal within the computational learning theory framework.