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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 7: The Canonical Distortion Measure for Vector Quantization and Function Approximation
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