Open Daily: 10am - 10pm | Alley door pickup 10am - 7pm 3038 Hennepin Ave Minneapolis, MN
612-822-4611

  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Evolutionary Learning: Advances in Theories and Algorithms

Evolutionary Learning: Advances in Theories and Algorithms

Yu, Yang
Qian, Chao
Zhou, Zhi-Hua

Hardcover

General ComputersProgramming

ISBN10: 9811359555
ISBN13: 9789811359552
Publisher: Springer Nature
Published: Jun 3 2019
Pages: 361
Weight: 1.55
Height: 0.88 Width: 6.14 Depth: 9.21
Language: English

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.

Also in

General Computers

View All