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Genetic Programming Theory and Practice XII

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Cover of 'Genetic Programming Theory and Practice XII'

Table of Contents

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    Book Overview
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    Chapter 1 Application of Machine-Learning Methods to Understand Gene Expression Regulation
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    Chapter 2 Identification of Novel Genetic Models of Glaucoma Using the “EMERGENT” Genetic Programming-Based Artificial Intelligence System
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    Chapter 3 Inheritable Epigenetics in Genetic Programming
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    Chapter 4 SKGP: The Way of the Combinator
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    Chapter 5 Sequential Symbolic Regression with Genetic Programming
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    Chapter 6 Sliding Window Symbolic Regression for Detecting Changes of System Dynamics
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    Chapter 7 Extremely Accurate Symbolic Regression for Large Feature Problems
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    Chapter 8 How to Exploit Alignment in the Error Space: Two Different GP Models
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    Chapter 9 Analyzing a Decade of Human-Competitive (“HUMIE”) Winners: What Can We Learn?
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    Chapter 10 Tackling the Boolean Multiplexer Function Using a Highly Distributed Genetic Programming System
Attention for Chapter 1: Application of Machine-Learning Methods to Understand Gene Expression Regulation
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