Abstract
The use of Rissanen's minimum description length principle for the construction of probabilistic acyclic automata (PAA) is explored. We propose a learning algorithm for a PAA that is adaptive both in the structure and the dimension of the model. The proposed algorithm was tested on synthetic data as well as on real pattern recognition problems.
Original language | English (US) |
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State | Published - 1994 |
Event | Proceedings of the 1994 IEEE International Symposium on Information Theory - Trodheim, Norw Duration: Jun 27 1994 → Jul 1 1994 |
Other
Other | Proceedings of the 1994 IEEE International Symposium on Information Theory |
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City | Trodheim, Norw |
Period | 6/27/94 → 7/1/94 |
All Science Journal Classification (ASJC) codes
- Theoretical Computer Science
- Information Systems
- Modeling and Simulation
- Applied Mathematics