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On metric divergences of probability measures

Igor Vajda (2009)

Kybernetika

Standard properties of φ -divergences of probability measures are widely applied in various areas of information processing. Among the desirable supplementary properties facilitating employment of mathematical methods is the metricity of φ -divergences, or the metricity of their powers. This paper extends the previously known family of φ -divergences with these properties. The extension consists of a continuum of φ -divergences which are squared metric distances and which are mostly new but include...

On naive Bayes in speech recognition

László Tóth, András Kocsor, János Csirik (2005)

International Journal of Applied Mathematics and Computer Science

The currently dominant speech recognition technology, hidden Mar-kov modeling, has long been criticized for its simplistic assumptions about speech, and especially for the naive Bayes combination rule inherent in it. Many sophisticated alternative models have been suggested over the last decade. These, however, have demonstrated only modest improvements and brought no paradigm shift in technology. The goal of this paper is to examine why HMM performs so well in spite of its incorrect bias due to...

On related transducers

Petr Lisoněk (1990)

Acta Universitatis Palackianae Olomucensis. Facultas Rerum Naturalium. Mathematica

On selecting the best features in a noisy environment

Jan Flusser, Tomáš Suk (1998)

Kybernetika

This paper introduces a novel method for selecting a feature subset yielding an optimal trade-off between class separability and feature space dimensionality. We assume the following feature properties: (a) the features are ordered into a sequence, (b) robustness of the features decreases with an increasing order and (c) higher-order features supply more detailed information about the objects. We present a general algorithm how to find under those assumptions the optimal feature subset. Its performance...

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