Most rule learning systems posit hard decision boundaries for continuous attributes and point estimates of rule accuracy, with no measures of variance, which may seem arbitrary to ...
Lemuel R. Waitman, Douglas H. Fisher, Paul H. King
Abstract. In this paper, an agent-based evolutionary computing technique is introduced, that is geared towards the automatic induction and optimization of grammars for natural lang...
This paper describes an agent-based evolutionary computing technique called GRAEL (Grammar Evolution), that is able to perform different natural language grammar optimization and ...
We consider the problem of optimally separating two multivariate populations. Robust linear discriminant rules can be obtained by replacing the empirical means and covariance in th...
This paper proposes a new bootstrapping approach to unsupervised part-of-speech induction. In comparison to previous bootstrapping algorithms developed for this problem, our appro...