Consider a Bayesian binary decision-making problem in star networks, where local agents make selfish decisions independently, and fusion agent makes final decision based on aggregated its own private signal. In particular, we assume all have beliefs for the true prior probability, which they perform making. We focus Bayes risk of counterintuitively find that incorrect could achieve smaller than...

An approach to improve accuracy of incorrect domain theories is presented that learns concept descriptions from positive and negative examples of the concept. The method uses the available domain theory, that might be both overly general and overly speci c, to group training examples before attempting concept induction. gentre is a system that has been implemented to test the performance of the...

Penalized likelihood method is among the most eeective tools for nonparametric multivari-ate function estimation. Recently, a generic computation-oriented asymptotic theory has been developed in the density estimation setting, and been extended to other settings such as conditional density estimation, regression, and hazard rate estimation, under the assumption that the true function resides in...