All the material that we have covered in class make up the syllabus, including the homework exercises. In terms of the course book, we have covered the following:
- Chapter 2 - Foundations
- All sections except 2.1.6.
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Chapter 3 - The Bayesian Network Representation
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All sections.
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Chapter 4 - Undirected Graphical Models
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All sections except 4.4.2 and 4.6.
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Chapter 9 - Exact Inference: Variable Elimination
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Only sections 9.2, 9.3, and 9.4.1-9.4.2.
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Chapter 10 - Exact Inference: Clique Trees
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All sections.
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Chapter 17 - Parameter Estimation
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All sections except 17.2.4, 17.5, and most of 17.6.
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Included from 17.6: 17.6.1 and 17.6.2.2 up til Lemma 17.2.
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Chapter 18 - Structure Learning in Bayesian Networks
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All sections except 18.4.4, 18.5, and 18.6.
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Chapter 20 - Learning Undirected Models
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All except 20.3.2-20.3.4, 20.4.2, 20.5, 20.6.2, and 20.7.4-20.7.5.
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Chapter 21 - Causality
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All except 21.4-21.6 and 21.7.4.
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