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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 Derivation Reduction of Metarules in Meta-interpretive Learning
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    Chapter 2 Large-Scale Assessment of Deep Relational Machines
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    Chapter 3 How Much Can Experimental Cost Be Reduced in Active Learning of Agent Strategies?
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    Chapter 4 Diagnostics of Trains with Semantic Diagnostics Rules
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    Chapter 5 The Game of Bridge: A Challenge for ILP
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    Chapter 6 Sampling-Based SAT/ASP Multi-model Optimization as a Framework for Probabilistic Inference
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    Chapter 7 Explaining Black-Box Classifiers with ILP – Empowering LIME with Aleph to Approximate Non-linear Decisions with Relational Rules
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    Chapter 8 Learning Dynamics with Synchronous, Asynchronous and General Semantics
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    Chapter 9 Was the Year 2000 a Leap Year? Step-Wise Narrowing Theories with Metagol
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    Chapter 10 Targeted End-to-End Knowledge Graph Decomposition
Attention for Chapter 6: Sampling-Based SAT/ASP Multi-model Optimization as a Framework for Probabilistic Inference
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