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Learning Logically Defined Hypotheses - Martin Grohe, RWTH Aachen University
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- 1 Intro
- 2 Outline
- 3 Declarative ML
- 4 Idea of Model-Theoretic Framework
- 5 Example 1 (cont d)
- 6 Example 2
- 7 Formal Framework For simplicity, we only consider Boolean classification problems
- 8 Learning as Minimisation
- 9 Remarks on VC-Dimension and PAC-Learning
- 10 Computation Model
- 11 Complexity Considerations
- 12 Proof
- 13 Strings as Background Structures
- 14 Learning with Local Access
- 15 Monadic Second-Order Logic
- 16 Building an Index
- 17 Factorisation Trees as Index Data Structures
- 18 Learning MSO
- 19 Pre-Processing
- 20 Learning Phase 1
- 21 Open Problems
