Augmented Statistical Models: Exploiting Generative Models in Discriminative Classifiers

Abstract

In recent years, many algorithms have been proposed for discriminative classification of data. Popular examples are support vector machines (SVMs) [1] and conditional random fields (CRFs) [2]. These techniques make extensive use of fixed-dimensional mappings from the observation-space to a (often high-dimensional) feature-space. Unfortunately, for… (More)

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