A key problem faced by classifiers is coping with styles not represented in the training set. We present an application of hierarchical Bayesian methods to the problem of recogniz...
Diffuse Optical Tomography (DOT) poses a typical illposed inverse problem with limited number of measurements and inherently low spatial resolution. In this paper, we propose a hi...
Murat Guven, Birsen Yazici, Xavier Intes, Britton ...
Traditional n-gram language models are widely used in state-of-the-art large vocabulary speech recognition systems. This simple model suffers from some limitations, such as overfi...
In this paper we address the problem of analyzing web log data collected at a typical online newspaper site. We propose a two-way clustering technique based on probability theory....
Hannes Wettig, Jussi Lahtinen, Tuomas Lepola, Petr...
Abstract. Multiply sectioned Bayesian networks (MSBNs) were originally proposed as a modular representation of uncertain knowledge by sectioning a large Bayesian network (BN) into ...