Deep Statistical Comparison for Meta-heuristic Stochastic Optimization Algorithms

Author:   Tome Eftimov ,  Peter Korošec
Publisher:   Springer Nature Switzerland AG
Edition:   1st ed. 2022
ISBN:  

9783030969196


Pages:   133
Publication Date:   12 June 2023
Format:   Paperback
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

Our Price $310.47 Quantity:  
Add to Cart

Share |

Deep Statistical Comparison for Meta-heuristic Stochastic Optimization Algorithms


Add your own review!

Overview

Full Product Details

Author:   Tome Eftimov ,  Peter Korošec
Publisher:   Springer Nature Switzerland AG
Imprint:   Springer Nature Switzerland AG
Edition:   1st ed. 2022
Weight:   0.244kg
ISBN:  

9783030969196


ISBN 10:   3030969193
Pages:   133
Publication Date:   12 June 2023
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

Table of Contents

Reviews

“The book is well written and the presentation is easy to follow. It will be useful to students and researchers dealing with metaheuristic stochastic optimization, but also to practitioners who want to know how to choose the best methods to solve the real-life problems they face.” (Marcin Anholcer, zbMATH 1504.90003, 2023)


Author Information

Tome Eftimov is currently a research fellow at the Jožef Stefan Institute, Ljubljana, Slovenia where he was awarded his PhD. He has since been a postdoctoral research fellow at the Dept. of Biomedical Data Science, and the Centre for Population Health Sciences, Stanford University, USA, and a research associate at the University of California, San Francisco, USA. His main areas of research include statistics, natural language processing, heuristic optimization, machine learning, and representational learning. His work related to benchmarking in computational intelligence is focused on developing more robust statistical approaches that can be used for the analysis of experimental data.  Peter Korošec received his PhD degree from the Jožef Stefan Postgraduate School, Ljubljana, Slovenia. Since 2002 he has been a researcher at the Computer Systems Department of the Jožef Stefan Institute, Ljubljana. He has participated in the organization of various conferencesworkshops as program chair or organizer. He has successfully applied his optimization approaches to several real-world problems in engineering. Recently, he has focused on better understanding optimization algorithms so that they can be more efficiently selected and applied to real-world problems.  The authors have presented the related tutorial at the significant related international conferences in Evolutionary Computing, including GECCO, PPSN, and SSCI.

Tab Content 6

Author Website:  

Customer Reviews

Recent Reviews

No review item found!

Add your own review!

Countries Available

All regions
Latest Reading Guide

wl

Shopping Cart
Your cart is empty
Shopping cart
Mailing List