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This paper presents a new framework of language model adaptation based on modification of structures of background corpus and language model. The widely used adaptation approach such as Linear Interpolation Method (LI) and Minimum Discrimination Information (MDI) method are used as the approaches to modify structure of trained background language model in new framework, while Maximum A Posteriori...
In this paper, we derive a maximum a posteriori (MAP) classifier using the features extracted by biased discriminant analysis (BDA) in multi-class classification problems. Using the one-against-the-rest scheme we construct several feature spaces, where the MAP classifier is formulated. Although the maximum likelihood (ML) classifier is generally equivalent to the MAP classifier when the prior probability...
In learning based single image super-resolution (SR) approach, the super-resolved image are usually found or combined from training database through patch matching. But because the representation ability of small patch is limited, it is difficult to guarantee that the super-resolved image is best under global view. To tackle this problem, we propose a statistical learning method for SR with both global...
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