Abstract. This paper presents an empirical study on four techniques of language model adaptation, including a maximum a posteriori (MAP) method and three discriminative training mo...
The study of common, complex multifactorial diseases in genetic epidemiology is complicated by nonlinearity in the genotype-to-phenotype mapping relationship that is due, in part,...
Ryan J. Urbanowicz, Nate Barney, Bill C. White, Ja...
Learning models for detecting and classifying object categories is a challenging problem in machine vision. While discriminative approaches to learning and classification have, in...
The choice of a color space is of great importance for many computer vision algorithms (e.g. edge detection and object recognition). It induces the equivalence classes to the actu...
In this paper, we investigate a simple, mistakedriven learning algorithm for discriminative training of continuous density hidden Markov models (CD-HMMs). Most CD-HMMs for automat...