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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 8: Lifelong Learning Algorithms
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Mentioned by

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2 news outlets
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8 Google+ users

Citations

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375 Dimensions

Readers on

mendeley
87 Mendeley
Summary News Google+ Dimensions citations
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Chapter title
Lifelong Learning Algorithms
Chapter number 8
Book title
Learning to Learn
Published by
Springer US, February 1998
DOI 10.1007/978-1-4615-5529-2_8
Book ISBNs
978-1-4613-7527-2, 978-1-4615-5529-2
Authors

Sebastian Thrun, Thrun, Sebastian

View on publisher site
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 87 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 3%
Ireland 1 1%
Unknown 83 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 19 22%
Student > Master 16 18%
Researcher 8 9%
Student > Doctoral Student 8 9%
Student > Bachelor 7 8%
Other 10 11%
Unknown 19 22%
Readers by discipline Count As %
Computer Science 46 53%
Engineering 8 9%
Social Sciences 2 2%
Medicine and Dentistry 2 2%
Nursing and Health Professions 1 1%
Other 7 8%
Unknown 21 24%

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