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Let us now derive a simple maximum entropy model.
This paper introduces a maximum entropy model (MEM -based speech synthesis.
Supervised sentiment detection of micro-blog messages (with a Maximum Entropy model).
The maximum entropy model was used for text classification, leading to the construction of an indicator for market sentiments.
In this paper, a maximum entropy model was used to drive the distribution expressed by the soft decision tree architecture.
Mei et al. [15] proposed WTLME which is based on maximum entropy model, using instance weighted technology.
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Environmental suitability was modelled using maximum entropy modelling (Maxent), a machine-learning process that uses presence-only data [6].
In order to alleviate this problem, this paper proposed HMEM as a new acoustic modeling technique based on maximum entropy modeling approach.
Open image in new window Fig. 10 Intrinsic vulnerability map obtained by applying maximum entropy modeling.
OSCAR3/4 are machine learning-based systems that utilize maximum entropy models [16] on the OSCAR corpus.
Contrastive divergence [17] is another popular method to estimate parameters in discrete maximum entropy models.
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