Dear Colleague,
Prof. Siarry and I are coming up with a ‘Optimization and Machine Leaning’
book in ISTE Editions. The book is planned to have different sections such
as Collective intelligence, Hybrid artificial intelligence approach, Design
parallel optimization based on artificial intelligence approaches, etc….
and its applications.
I invite you to write a chapter on which may include a detailed literature
review, detailed theoretical and mathematical formulation of the method,
benchmarking and validation with a detailed illustrative/example solution
steps, solution to a real world application (if possible) and computer code
(any computer language).
The expected date of full chapter submission is November 30, 2020.
If you agree, then please email me 'probable title of the chapter' and the
'list of coauthors along with affiliations'.
Best Regards
Chelouah
*Title of the book*
*Optimization and Machine Learning*
*Aim of the book *
The fields of machine learning and optimization are highly interwoven.
Optimization problems forms the core of machine learning methods and modern
optimization algorithms are increasingly using machine learning to improve
their efficiency. L'apprentissage automatique et l'optimisation partagent
trois composantes: la représentation, l'évaluation et la recherche
itérative. Machine learning and optimization find applications in all areas
of science. There are many learning methods, each using a different
algorithmic structure to optimize predictions based on the data received.
Therefore, the first objective of this book will be to shed light on the
key principles and methods that are common to both fields.
Quite recently, modern approaches to machine learning have also been
applied to the design of optimization algorithms themselves, taking
advantage of their ability to capture valuable information from complex
structures in large spaces. This book is thus focused on a common field of
research: how to solve new machine learning problems with robust
optimization solvers and how to use new optimization methods for existing
machine learning problems.
*Recommended topics include, but are not limited to the following:*
· *Theory*
· Collective intelligence, teamwork, coalition, distributed problem
solving
· Algorithms based on Artificial and Natural Intelligence (Swarm
intelligence, Bee colony optimization, Ant colony optimization, Genetic
algorithm)
· A framework for combining artificial intelligence and optimization
in engineering
· Hybrid artificial intelligence approach based on metaheuristic
optimization
· Design parallel optimization based on artificial intelligence
approaches
· Artificial intelligence in hard complex system optimization
· *Applications *
· Artificial intelligence & Optimization in (data analysis,
transportation, healthcare, IOT,…)
*Important dates*
– Chapter proposal NOW (with chapter title, and names &
affiliations of authors)
– Chapter submission November, 30th 2020
– Notification to authors January, 30th 2021
– Camera-ready chapters March, 30th 2021
– Publication: June, 1st 2021
*Address for submission *
Please use this link https://easychair.org/conferences/?conf=oml2020
*Information*
For any information please contact the guest editors
Rachid Chelouah, Researcher at CY Cergy Paris University, France
[log in to unmask]
Patrick Siarry, Professor at University-Paris-Est Creteil, France
[log in to unmask]
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