We propose and analyze a distribution learning algorithm for a subclass of acyclic probalistic finite automata (APFA). This subclass is characterized by a certain distinguishability property of the automata's states. Though hardness results are known for learning distributions generated by general A
On the Languages Representable by Finite Probabilistic Automata
✍ Scribed by Phan Dinh Diêu
- Publisher
- John Wiley and Sons
- Year
- 1971
- Tongue
- English
- Weight
- 837 KB
- Volume
- 17
- Category
- Article
- ISSN
- 0044-3050
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