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Inductive Logic Programming

Overview of attention for book
Cover of 'Inductive Logic Programming'

Table of Contents

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    Book Overview
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    Chapter 1 Relational Affordance Learning for Task-Dependent Robot Grasping
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    Chapter 2 Positive and Unlabeled Relational Classification Through Label Frequency Estimation
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    Chapter 3 On Applying Probabilistic Logic Programming to Breast Cancer Data
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    Chapter 4 Logical Vision: One-Shot Meta-Interpretive Learning from Real Images
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    Chapter 5 Demystifying Relational Latent Representations
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    Chapter 6 Parallel Online Learning of Event Definitions
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    Chapter 7 Relational Restricted Boltzmann Machines: A Probabilistic Logic Learning Approach
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    Chapter 8 Parallel Inductive Logic Programming System for Superlinear Speedup
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    Chapter 9 Inductive Learning from State Transitions over Continuous Domains
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    Chapter 10 Stacked Structure Learning for Lifted Relational Neural Networks
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    Chapter 11 Pruning Hypothesis Spaces Using Learned Domain Theories
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    Chapter 12 An Investigation into the Role of Domain-Knowledge on the Use of Embeddings
Attention for Chapter 8: Parallel Inductive Logic Programming System for Superlinear Speedup
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