Open Daily: 10am - 10pm | Alley door pickup 10am - 7pm 3038 Hennepin Ave Minneapolis, MN
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  • 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
Black Box Optimization, Machine Learning, and No-Free Lunch Theorems

Black Box Optimization, Machine Learning, and No-Free Lunch Theorems

Rasskazova, Varvara
Vrahatis, Michael N.
Pardalos, Panos M.

Hardcover

Series: Springer Optimization and Its Applications, Book 170

General ComputersGeneral Mathematics

ISBN10: 3030665143
ISBN13: 9783030665142
Publisher: Springer
Published: Jun 27 2021
Pages: 388
Weight: 1.62
Height: 0.88 Width: 6.14 Depth: 9.21
Language: English

This edited volume illustrates the connections between machine learning techniques, black box optimization, and no-free lunch theorems. Each of the thirteen contributions focuses on the commonality and interdisciplinary concepts as well as the fundamentals needed to fully comprehend the impact of individual applications and problems. Current theoretical, algorithmic, and practical methods used are provided to stimulate a new effort towards innovative and efficient solutions. The book is intended for beginners who wish to achieve a broad overview of optimization methods and also for more experienced researchers as well as researchers in mathematics, optimization, operations research, quantitative logistics, data analysis, and statistics, who will benefit from access to a quick reference to key topics and methods. The coverage ranges from mathematically rigorous methods to heuristic and evolutionary approaches in an attempt to equip the reader with different viewpoints of the same problem.

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