In designing learning algorithms it seems quite reasonable to construct them in such a way that all data the algorithm already has obtained are correctly and completely reflected...
Abstract— In this paper, the Independence Relative Map algorithm is presented. The algorithm aims to achieve the independence of relative map states. We show that using dependent...
Predictive accuracy has been used as the main and often only evaluation criterion for the predictive performance of classification learning algorithms. In recent years, the area ...
In many real-world domains, undirected graphical models such as Markov random fields provide a more natural representation of the dependency structure than directed graphical mode...
Sushmita Roy, Terran Lane, Margaret Werner-Washbur...
We document a connection between constraint reasoning and probabilistic reasoning. We present an algorithm, called probabilistic arc consistency, which is both a generalization of...