Automated Design of Machine Learning and Search Algorithms /

This book presents recent advances in automated machine learning (AutoML) and automated algorithm design and indicates the future directions in this fast-developing area. Methods have been developed to automate the design of neural networks, heuristics and metaheuristics using techniques such as met...

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Bibliographic Details
Corporate Author:	SpringerLink (Online service)
Other Authors:	Pillay, Nelishia (Editor), Qu, Rong (Editor)
Format:	eBook
Language:	English
Published:	Cham : Springer International Publishing : Imprint: Springer, 2021.
Edition:	1st ed. 2021.
Series:	Natural Computing Series
Subjects:	Artificial intelligence. Artificial Intelligence. Electronic books.
Online Access:	Connect to the full text of this electronic book

Table of Contents:

Chapter 1: Recent Developments of Automated Machine Learning and Search Techniques
Chapter 2: Automated Machine Learning
Chapter 3: A General Model for Automated Algorithm Design
Chapter 4: Rigorous Performance Analysis of Hyper-Heuristics
Chapter 5: AutoMoDe
Chapter 6: A cross-domain method for generation of constructive and perturbative heuristics
Chapter 7: Hyper-heuristics
Chapter 8: Towards Real-time Federated Evolutionary Neural
Chapter 9: Knowledge Transfer in Genetic Programming
Chapter 10: Automated Design of Classification Algorithms
Chapter 11: Automated Design (AutoDes).