An introduction to computational learning theory /
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| Format: | Book |
| Language: | English |
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Cambridge, Mass. :
MIT Press,
c1994.
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Table of Contents:
- 1. The Probably Approximately Correct Learning Model
- 2. Occam's Razor
- 3. The Vapnik-Chervonenkis Dimension
- 4. Weak and Strong Learning
- 5. Learning in the Presence of Noise
- 6. Inherent Unpredictability
- 7. Reducibility in PAC Learning
- 8. Learning Finite Automata by Experimentation
- 9. Appendix: Some Tools for Probabilistic Analysis.