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...
Enforcing arc consistency (AC) during search has proven to be a very effective method in solving Constraint Satisfaction Problems and it has been widely-used in many Constraint Pr...
Chavalit Likitvivatanavong, Yuanlin Zhang, Scott S...
We study statistical consistency of two recently proposed subspace identification algorithms for closed-loop systems. These algorithms een as implementations of an abstract state-...