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About the Book and Supporting Material

Željko Ivezi, Andrew J. Connolly, Jacob T. VanderPlas, Alexander Gray, Željko Ivezi, Andrew J. Connolly, Jacob T. VanderPlas, and Alexander Gray

in Statistics, Data Mining, and Machine Learning in Astronomy: A Practical Python Guide for the Analysis of Survey Data

Published in print:
2014
Published Online:
October 2017
ISBN:
9780691151687
eISBN:
9781400848911
Item type:
chapter
Publisher:
Princeton University Press
DOI:
10.23943/princeton/9780691151687.003.0001
Subject:
Physics, Particle Physics / Astrophysics / Cosmology

This chapter begins by discussing the meaning of data mining, machine learning, and knowledge discovery. Data mining, machine learning, and knowledge discovery refer to research areas which can all ... More


Fast Computation on Massive Data Sets

Željko Ivezi, Andrew J. Connolly, Jacob T. VanderPlas, Alexander Gray, Željko Ivezi, Andrew J. Connolly, Jacob T. VanderPlas, and Alexander Gray

in Statistics, Data Mining, and Machine Learning in Astronomy: A Practical Python Guide for the Analysis of Survey Data

Published in print:
2014
Published Online:
October 2017
ISBN:
9780691151687
eISBN:
9781400848911
Item type:
chapter
Publisher:
Princeton University Press
DOI:
10.23943/princeton/9780691151687.003.0002
Subject:
Physics, Particle Physics / Astrophysics / Cosmology

This chapter describes basic concepts and tools for tractably performing the computations described in the rest of this book. The need for fast algorithms for such analysis subroutines is becoming ... More


The Necessity of Order in Machine Learning: Is Order in Order?

A. Cornuéjols

in In Order to Learn: How the sequence of topics influences learning

Published in print:
2007
Published Online:
April 2010
ISBN:
9780195178845
eISBN:
9780199893751
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/acprof:oso/9780195178845.003.0003
Subject:
Psychology, Cognitive Psychology

This chapter provides a detailed introduction to, and overview of, the theories from machine learning, and introduces some of the basic theoretical concepts and models from computational studies of ... More


Epilogue: Let’s Educate

Oliver G. Selfridge

in In Order to Learn: How the sequence of topics influences learning

Published in print:
2007
Published Online:
April 2010
ISBN:
9780195178845
eISBN:
9780199893751
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/acprof:oso/9780195178845.003.0016
Subject:
Psychology, Cognitive Psychology

This chapter contends that there is much we can learn about the education of people by studying learning in machines. Indeed, machine learning (ML) is an important major part of artificial ... More


Machine Learning in Non-Stationary Environments: Introduction to Covariate Shift Adaptation

Masashi Sugiyama and Motoaki Kawanabe

Published in print:
2012
Published Online:
September 2013
ISBN:
9780262017091
eISBN:
9780262301220
Item type:
book
Publisher:
The MIT Press
DOI:
10.7551/mitpress/9780262017091.001.0001
Subject:
Computer Science, Machine Learning

As the power of computing has grown over the past few decades, the field of machine learning has advanced rapidly in both theory and practice. Machine learning methods are usually based on the ... More


Exploration in Predictive Analysis and Machine Learning

Kelly G. Stepura, Jim Schwab, Donald J. Baumann, Natalie Sowinski, and Stephanie Thorne

in Decision-Making and Judgment in Child Welfare and Protection: Theory, Research, and Practice

Published in print:
2020
Published Online:
August 2020
ISBN:
9780190059538
eISBN:
9780190059569
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/oso/9780190059538.003.0002
Subject:
Social Work, Children and Families

This chapter explores the potential for using machine learning methods to support foster care workers by improving the accuracy of the complex but critical decisions they make on behalf of children, ... More


Rules of Order: Process Models of Human Learning

Josef Nerb, Frank E. Ritter, and Pat Langley

in In Order to Learn: How the sequence of topics influences learning

Published in print:
2007
Published Online:
April 2010
ISBN:
9780195178845
eISBN:
9780199893751
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/acprof:oso/9780195178845.003.0004
Subject:
Psychology, Cognitive Psychology

Science is concerned not only with data, but also with models or theories that explain those data. Because human cognition is dynamic and involves change over time, accounts of cognition often take ... More


The Effects of Order: A Constraint-Based Explanation

Stellan Ohlsson

in In Order to Learn: How the sequence of topics influences learning

Published in print:
2007
Published Online:
April 2010
ISBN:
9780195178845
eISBN:
9780199893751
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/acprof:oso/9780195178845.003.0011
Subject:
Psychology, Cognitive Psychology

This chapter presents a computational model that shows how information migrates from declarative to procedural knowledge and provides a powerful new learning mechanism for machine-learning ... More


Learning Machine Translation

Cyril Goutte, Nicola Cancedda, Marc Dymetman, and George Foster (eds)

Published in print:
2008
Published Online:
August 2013
ISBN:
9780262072977
eISBN:
9780262255097
Item type:
book
Publisher:
The MIT Press
DOI:
10.7551/mitpress/9780262072977.001.0001
Subject:
Computer Science, Machine Learning

The Internet gives us access to a wealth of information in languages we don’t understand. The investigation of automated or semi-automated approaches to translation has become a thriving research ... More


In Order to Learn: How the sequence of topics influences learning

Frank E. Ritter, Josef Nerb, Erno Lehtinen, and Timothy O'Shea (eds)

Published in print:
2007
Published Online:
April 2010
ISBN:
9780195178845
eISBN:
9780199893751
Item type:
book
Publisher:
Oxford University Press
DOI:
10.1093/acprof:oso/9780195178845.001.0001
Subject:
Psychology, Cognitive Psychology

Order affects the results you get: different orders of presenting material can lead to qualitatively and quantitatively different learning outcomes. These differences occur in both natural and ... More


Conclusions and Future Prospects

Masashi Sugiyama and Motoaki Kawanabe

in Machine Learning in Non-Stationary Environments: Introduction to Covariate Shift Adaptation

Published in print:
2012
Published Online:
September 2013
ISBN:
9780262017091
eISBN:
9780262301220
Item type:
chapter
Publisher:
The MIT Press
DOI:
10.7551/mitpress/9780262017091.003.0011
Subject:
Computer Science, Machine Learning

This chapter summarizes the main themes covered in the preceding discussions and discusses future prospects. This book has provided a comprehensive overview of theory, algorithms, and applications of ... More


The Quest for Intelligent Machines

Arlindo Oliveira

in The Digital Mind: How Science is Redefining Humanity

Published in print:
2017
Published Online:
September 2017
ISBN:
9780262036030
eISBN:
9780262338394
Item type:
chapter
Publisher:
The MIT Press
DOI:
10.7551/mitpress/9780262036030.003.0005
Subject:
Computer Science, Artificial Intelligence

This chapter addresses the question of whether a computer can become intelligent and how to test for that possibility. It introduces the idea of the Turing test, a test developed to determine, in an ... More


Morphological analogy: Only a beginning

John Goldsmith

in Analogy in Grammar: Form and Acquisition

Published in print:
2009
Published Online:
September 2009
ISBN:
9780199547548
eISBN:
9780191720628
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/acprof:oso/9780199547548.003.0007
Subject:
Linguistics, Psycholinguistics / Neurolinguistics / Cognitive Linguistics, Computational Linguistics

A range of approaches to word structure assume segmentation of words into morphs. This chapter proposes explicit algorithm that takes natural language text as its input, and produces the ... More


A Statistical Machine Translation Primer

Nicola Cancedda, Marc Dymetman, George Foster, and Cyril Goutte

in Learning Machine Translation

Published in print:
2008
Published Online:
August 2013
ISBN:
9780262072977
eISBN:
9780262255097
Item type:
chapter
Publisher:
The MIT Press
DOI:
10.7551/mitpress/9780262072977.003.0001
Subject:
Computer Science, Machine Learning

This chapter provides an introduction to the main aspects of statistical machine translation (SMT). The discussions cover automatic evaluation of machine translation output, language modeling, ... More


Fundamentals of Machine Learning

Thomas P. Trappenberg

Published in print:
2019
Published Online:
January 2020
ISBN:
9780198828044
eISBN:
9780191883873
Item type:
book
Publisher:
Oxford University Press
DOI:
10.1093/oso/9780198828044.001.0001
Subject:
Neuroscience, Behavioral Neuroscience

Machine learning is exploding, both in research and for industrial applications. This book aims to be a brief introduction to this area given the importance of this topic in many disciplines, from ... More


The Impact of Machine Learning on Economics

Susan Athey

in The Economics of Artificial Intelligence: An Agenda

Published in print:
2019
Published Online:
January 2020
ISBN:
9780226613338
eISBN:
9780226613475
Item type:
chapter
Publisher:
University of Chicago Press
DOI:
10.7208/chicago/9780226613475.003.0021
Subject:
Economics and Finance, Microeconomics

This chapter provides an assessment of the early contributions of machine learning to economics, as well as predictions about its future contributions. It begins by briefly overviewing some themes ... More


A Short Introduction to the Ethics of Artificial Intelligence

S. Matthew Liao

in Ethics of Artificial Intelligence

Published in print:
2020
Published Online:
October 2020
ISBN:
9780190905033
eISBN:
9780190905071
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/oso/9780190905033.003.0001
Subject:
Philosophy, Moral Philosophy

This introduction outlines in section I.1 some of the key issues in the study of the ethics of artificial intelligence (AI) and proposes ways to take these discussions further. Section I.2 discusses ... More


Artificial Intelligence, Economics, and Industrial Organization

Hal Varian

in The Economics of Artificial Intelligence: An Agenda

Published in print:
2019
Published Online:
January 2020
ISBN:
9780226613338
eISBN:
9780226613475
Item type:
chapter
Publisher:
University of Chicago Press
DOI:
10.7208/chicago/9780226613475.003.0016
Subject:
Economics and Finance, Microeconomics

Machine learning (ML) and artificial intelligence (AI) have been around for many years. However, in the last five years, remarkable progress has been made using multilayered neural networks in ... More


Alignment for Advanced Machine Learning Systems

Jessica Taylor, Eliezer Yudkowsky, Patrick LaVictoire, and Andrew Critch

in Ethics of Artificial Intelligence

Published in print:
2020
Published Online:
October 2020
ISBN:
9780190905033
eISBN:
9780190905071
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/oso/9780190905033.003.0013
Subject:
Philosophy, Moral Philosophy

This chapter surveys eight research areas organized around one question: As learning systems become increasingly intelligent and autonomous, what design principles can best ensure that their behavior ... More


Can an Algorithm Be Disturbed?: Machine Learning, Intrinsic Criticism, and the Digital Humanities

James E. Dobson

in Critical Digital Humanities: The Search for a Methodology

Published in print:
2019
Published Online:
September 2019
ISBN:
9780252042270
eISBN:
9780252051111
Item type:
chapter
Publisher:
University of Illinois Press
DOI:
10.5622/illinois/9780252042270.003.0002
Subject:
Literature, Criticism/Theory

This chapter positions the use of machine learning within the digital humanities as part of a wider movement that nostalgically seeks to return literary criticism to the structuralist era, to a ... More


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