利用最小描述长度原理推断概率无循环自动机

Proceedings of 1994 IEEE International Symposium on Information Theory Pub Date : 1994-12-01 DOI:10.1109/ISIT.1994.394627

Y. Singer, Naftali Tishby

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引用次数: 3

摘要

探讨了利用Rissanen(1978)的最小描述长度原理构造概率无循环自动机(PAA)。我们提出了一种PAA的学习算法，该算法在模型的结构和维度上都是自适应的。该算法在合成数据和实际模式识别问题上进行了测试。

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Inferring probabilistic acyclic automata using the minimum description length principle

The use of Rissanen's (1978) 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.<>

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Proceedings of 1994 IEEE International Symposium on Information Theory

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