Evolutionary Learning: Advances in Theories and Algorithms

• Κύριοι συγγραφείς: Zhou, Zhi-Hua (Συγγραφέας, http://id.loc.gov/vocabulary/relators/aut), Yu, Yang (http://id.loc.gov/vocabulary/relators/aut), Qian, Chao (http://id.loc.gov/vocabulary/relators/aut)
• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Singapore : Springer Singapore : Imprint: Springer, 2019.
• Έκδοση: 1st ed. 2019.
• Θέματα: Artificial intelligence.; Algorithms.; Computer science-Mathematics.; Artificial Intelligence.; Algorithm Analysis and Problem Complexity.; Math Applications in Computer Science.

Many machine learning tasks involve solving complex optimization problems, such as working on non-differentiable, non-continuous, and non-unique objective functions; in some cases it can prove difficult to even define an explicit objective function. Evolutionary learning applies evolutionary algorit...

Πίνακας περιεχομένων:

• 1.Introduction
• 2. Preliminaries
• 3. Running Time Analysis: Convergence-based Analysis
• 4. Running Time Analysis: Switch Analysis
• 5. Running Time Analysis: Comparison and Unification
• 6. Approximation Analysis: SEIP
• 7. Boundary Problems of EAs
• 8. Recombination
• 9. Representation
• 10. Inaccurate Fitness Evaluation
• 11. Population
• 12. Constrained Optimization
• 13. Selective Ensemble
• 14. Subset Selection
• 15. Subset Selection: k-Submodular Maximization
• 16. Subset Selection: Ratio Minimization
• 17. Subset Selection: Noise
• 18. Subset Selection: Acceleration. .