Clustering is often formulated as a discrete optimization problem. The objective is to find, among all partitions of the data set, the best one according to some quality measure....
The stochastic discrimination (SD) theory considers learning as building models of uniform coverage over data distributions. Despite successful trials of the derived SD method in s...
Abstract. Response surfaces are a powerful tool for both classification and regression as they are able to model many different phenomena and construct complex boundaries between c...
In studying image quality and image preference it is necessary to collect psychophysical data. A variety of methods are used to arrive at interval scale values which indicate the ...
A central problem in learning in complex environmentsis balancing exploration of untested actions against exploitation of actions that are known to be good. The benefit of explora...