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Probability of events associational, interventional, counterfactual
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Classroom Contents
Optimizing Causal Objective Functions - Algorithms and Complexity
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- 1 Causal objective functions: What and why?
- 2 The causal hierarchy
- 3 Structural causal models SCM
- 4 The identifiability/learning dimension
- 5 Unit selection: The work of Li & Pearl
- 6 The algorithmic dimension of unit selection optimization
- 7 Examples of causal objective functions
- 8 Syntax and semantics of causal objective functions
- 9 Sub-models
- 10 Worlds
- 11 Events associational, interventional, counterfactual
- 12 Satisfaction of an event by a world
- 13 Example of satisfaction
- 14 Probability of events associational, interventional, counterfactual
- 15 Generalized events: conjunctive, disjunctive and negated
- 16 Variable elimination for computing associational queries
- 17 MAR marginals
- 18 MAP maximum a posteriori hypothesis
- 19 Treewidth & elimination orders
- 20 Optimizing causal objective functions
- 21 Triplet models: evaluating counterfactual queries
- 22 Objective models: optimizing the causal objective function using Reverse-MAP
- 23 Reverse-MAP: Relation to MAP, complexity class of Reverse-MAP and unit selection
- 24 Reverse-MAP: Algorithm, complexity bound, experiments
- 25 Elimination orders and treewidth of parallel worlds twin, triplet, .., models
- 26 Causal treewidth
- 27 Main messages
