Foundations of Computational Intelligence Volume 1 Learning and Approximation

Free Download Foundations of Computational Intelligence Volume 1: Learning and Approximation by Aboul-Ella Hassanien, Ajith Abraham, Athanasios V. Vasilakos, Witold Pedrycz
English | PDF | 2009 | 400 Pages | ISBN : 3642010814 | 8.07 MB
Foundations of Computational Intelligence Volume 1: Learning and Approximation: Theoretical Foundations and Applications Learning methods and approximation algorithms are fundamental tools that deal with computationally hard problems and problems in which the input is gradually disclosed over time. Both kinds of problems have a large number of applications arising from a variety of fields, such as algorithmic game theory, approximation classes, coloring and partitioning, competitive analysis, computational finance, cuts and connectivity, inapproximability results, mechanism design, network design, packing and covering, paradigms for design and analysis of approxi- tion and online algorithms, randomization techniques, real-world applications, scheduling problems and so on.