A sequential decision problem, based on the task of identifying the species of trees given acoustic echo data collected from them, is considered with well-known stochastic classifi...
We show the potential for classifying images of mixtures of aggregate, based themselves on varying, albeit well-defined, sizes and shapes, in order to provide a far more effective...
We investigate the effectiveness of GP-generated intelligent structures in classification tasks. Specifically, we present and use four context-free grammars to describe (1) decisi...
We present a novel framework for integrating prior knowledge into discriminative classifiers. Our framework allows discriminative classifiers such as Support Vector Machines (SVMs...
A maximum-entropy approach to generative similarity-based classifiers model is proposed. First, a descriptive set of similarity statistics is assumed to be sufficient for classifi...