This paper investigates the problem of incorporating auxiliary information (e.g. pitch) for speech recognition using dynamic Bayesian networks (DBNs). Previous works usually model...
A major difficulty in building Bayesian network models is the size of conditional probability tables, which grow exponentially in the number of parents. One way of dealing with th...
We present two algorithms for learning large-scale gene regulatory networks from microarray data: a modified informationtheory-based Bayesian network algorithm and a modified asso...
Zan Huang, Jiexun Li, Hua Su, George S. Watts, Hsi...
Bayesian network models are widely used for discriminative prediction tasks such as classification. Usually their parameters are determined using 'unsupervised' methods ...
We present further developments in our work on using data from real users to build a probabilistic model of user affect based on Dynamic Bayesian Networks (DBNs) and designed to de...