This paper describes initial testing of a novel idea to combine a CGP with an EDA. In recent work a new improved crossover technique was successfully applied to a CGP. To implemen...
We consider the multi-class classification problem, based on vector observation sequences, where the conditional (given class observations) probability distributions for each class...
Mostexisting decision-theoretic planners represent uncertainty about the state of the world with a precisely specified probability distribution over world states. This representat...
We present an efficient method within an active vision framework for recognizing objects which are ambiguous from certain viewpoints. The system is allowed to reposition the camer...
Hermann Borotschnig, Lucas Paletta, Manfred Prantl...
The problem of routing traffic through a congested network is studied. The framework is that introduced by Koutsoupias and Papadimitriou where the network is constituted by m paral...
We describe the g-factor which relates probability distributions on image features to distributions on the images themselves. The g-factor depends only on our choice of features a...
Accurately estimating probabilities from observations is important for probabilistic-based approaches to problems in computational biology. In this paper we present a biologically...
A major difficulty in building Bayesian network models is the size of conditional probability tables, which grow exponentially in the number of parents. One way of dealing with th...
Bayesian network is a popular modeling tool for uncertain domains that provides a compact representation of a joint probability distribution among a set of variables. Even though ...
We discuss existing approaches to train LR parsers, which have been used for statistical resolution of structural ambiguity. These approaches are nonoptimal, in the sense that a c...