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Learning to Learn

Overview of attention for book
Cover of 'Learning to Learn'

Table of Contents

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    Book Overview
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    Chapter 1 Learning to Learn: Introduction and Overview
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    Chapter 2 A Survey of Connectionist Network Reuse Through Transfer
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    Chapter 3 Transfer in Cognition
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    Chapter 4 Theoretical Models of Learning to Learn
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    Chapter 5 Multitask Learning
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    Chapter 6 Making a Low-Dimensional Representation Suitable for Diverse Tasks
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    Chapter 7 The Canonical Distortion Measure for Vector Quantization and Function Approximation
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    Chapter 8 Lifelong Learning Algorithms
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    Chapter 9 The Parallel Transfer of Task Knowledge Using Dynamic Learning Rates Based on a Measure of Relatedness
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    Chapter 10 Clustering Learning Tasks and the Selective Cross-Task Transfer of Knowledge
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    Chapter 11 Child: A First Step Towards Continual Learning
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    Chapter 12 Reinforcement Learning with Self-Modifying Policies
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    Chapter 13 Creating Advice-Taking Reinforcement Learners
Attention for Chapter 4: Theoretical Models of Learning to Learn
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Citations

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375 Dimensions

Readers on

mendeley
67 Mendeley
Summary Dimensions citations
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Chapter title
Theoretical Models of Learning to Learn
Chapter number 4
Book title
Learning to Learn
Published by
Springer, Boston, MA, January 1998
DOI 10.1007/978-1-4615-5529-2_4
Book ISBNs
978-1-4613-7527-2, 978-1-4615-5529-2
Authors

Jonathan Baxter, Baxter, Jonathan

View on publisher site
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 67 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 1%
Netherlands 1 1%
United States 1 1%
Germany 1 1%
Unknown 63 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 15 22%
Student > Master 10 15%
Researcher 10 15%
Student > Bachelor 7 10%
Professor 4 6%
Other 8 12%
Unknown 13 19%
Readers by discipline Count As %
Computer Science 33 49%
Engineering 7 10%
Social Sciences 3 4%
Agricultural and Biological Sciences 2 3%
Neuroscience 2 3%
Other 6 9%
Unknown 14 21%

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