Machine learning

Xin YAO; Yong LIU

doi:10.1007/0-387-28356-0_12

Machine learning

Xin YAO, Yong LIU

Research output: Book Chapters | Papers in Conference Proceedings › Book Chapter › Research › peer-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. © 2005 Springer Science+Business Media, LLC.

Original language	English
Title of host publication	Search Methodologies : Introductory Tutorials in Optimization and Decision Support Techniques
Editors	Edmund K. BURKE, Graham KENDALL
Publisher	Springer New York
Chapter	12
Pages	341-373
Number of pages	33
Edition	1st
ISBN (Electronic)	9780387283562
ISBN (Print)	9780387234601
DOIs	https://doi.org/10.1007/0-387-28356-0_12
Publication status	Published - 2005
Externally published	Yes

Bibliographical note

Introductory Tutorials in Search, Optimization and Decision Support Methodologies (INTROS)

Keywords

Neural Network
Machine Learning
Learning Algorithm
Connection Weight
Inductive Logic Programming

Access to Document

10.1007/0-387-28356-0_12

Cite this

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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. {\textcopyright} 2005 Springer Science+Business Media, LLC.",

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AU - YAO, Xin

AU - LIU, Yong

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N2 - 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. © 2005 Springer Science+Business Media, LLC.

AB - 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. © 2005 Springer Science+Business Media, LLC.

KW - Neural Network

KW - Machine Learning

KW - Learning Algorithm

KW - Connection Weight

KW - Inductive Logic Programming

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BT - Search Methodologies : Introductory Tutorials in Optimization and Decision Support Techniques

A2 - BURKE, Edmund K.

A2 - KENDALL, Graham

PB - Springer New York

ER -

Machine learning

Abstract

Bibliographical note

Keywords

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Machine learning

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