Machine learning

Xin YAO*, Yong LIU

*Corresponding author for this work

Research output: Book Chapters | Papers in Conference ProceedingsBook ChapterResearchpeer-review

5 Citations (Scopus)

Abstract

Machine learning is a very active sub-field of artificial intelligence concerned with the development of computational models of learning. Machine learning is inspired by the work in several disciplines: Cognitive sciences, computer science, statistics, computational complexity, information theory, control theory, philosophy and biology. Simply speaking, machine learning is learning by machine. From a computational point of view, machine learning refers to the ability of a machine to improve its performance based on previous results. From a biological point of view, machine learning is the study of how to create computers that will learn from experience and modify their activity based on that learning as opposed to traditional computers whose activity will not change unless the programmer explicitly changes it. © Springer Science+Business Media New York 2014.
Original languageEnglish
Title of host publicationSearch Methodologies : Introductory Tutorials in Optimization and Decision Support Techniques, Second Edition
EditorsEdmund K. BURKE, Graham KENDALL
PublisherSpringer US
Chapter17
Pages477-518
Number of pages42
Edition2nd
ISBN (Electronic)9781461469407
ISBN (Print)9781461469407
DOIs
Publication statusPublished - 2014
Externally publishedYes

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  • Machine learning

    YAO, X. & LIU, Y., 2005, Search Methodologies : Introductory Tutorials in Optimization and Decision Support Techniques. BURKE, E. K. & KENDALL, G. (eds.). 1st ed. Springer New York, p. 341-373 33 p.

    Research output: Book Chapters | Papers in Conference ProceedingsBook ChapterResearchpeer-review

    5 Citations (Scopus)

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