The use of Bayesian networks for classification problems has received significant recent attention. Although computationally efficient, the standard maximum likelihood learning me...
Kernel conditional random fields (KCRFs) are introduced as a framework for discriminative modeling of graph-structured data. A representer theorem for conditional graphical models...
This paper considers the problem of obtaining an accurate spectral representation of speech formant structure when the voicing source exhibits a high fundamental frequency. Our wo...
— We present a computational model of human category learning that learns the essential structures of the categories by forgetting information that is not useful for the given ta...
A huge diversity of biological databases is available via the Internet, but many of these databases have been developed in an ad hoc manner rather than in accordance with any data...