Zhi-Hua Zhou / Chao Qian / Yang Yu
Evolutionary Learning: Advances in Theories and Algorithms
- Springer Nature Singapore
- 2019
- Gebunden
- 376 Seiten
- ISBN 9789811359552
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 algorithms to address optimization problems in machine learning, and has yielded encouraging outcomes in many applications. However, due to the heuristic nature of evolutionary optimization, most outcomes to date have been empirical and lack theoretical support. This shortcoming has kept evolutionary learning from being well received in the machine learning community, which favors solid theoretical approaches. Recently there have been considerable efforts to address this issue. This book presents
Mehr
Weniger
zzgl. Versand
in Kürze