This paper considers a method that combines ideas from Bayesian learning, Bayesian network inference, and classical hypothesis testing to produce a more reliable and robust test o...
Bayesian Kullback Ying—Yang dependence reduction system and theory is presented. Via stochastic approximation, implementable algorithms and criteria are given for parameter lear...
Abstract. We present an approach to inferring probabilistic models of generegulatory networks that is intended to provide a more mechanistic representation of transcriptional regul...
In this paper, we show that the LVQ learning algorithm converges to locally asymptotic stable equilibria of an ordinary differential equation. We show that the learning algorithm ...
The goal of IT governance is not only to achieve internal efficiency in an IT organization, but also to support IT's role as a business enabler. The latter is here denoted IT ...