The maximum entropy method has recently been successfully introduced to a variety of natural language applications. In each of these applications, however, the power of the maximum entropy method is achieved at the cost of a considerable increase in computational requirements. In this paper we present a technique, closely related to the classical cluster expansion from statistical mechanics, for reducing the computational demands necessary to calculate conditional maximum entropy language models.
CITATION STYLE
Lafferty, J. D., & Suhm, B. (1996). Cluster Expansions and Iterative Scaling for Maximum Entropy Language Models. In Maximum Entropy and Bayesian Methods (pp. 195–202). Springer Netherlands. https://doi.org/10.1007/978-94-011-5430-7_23
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