— Modeling robot motion planning with uncertainty in a Bayesian framework leads to a computationally intractable stochastic control problem. We seek hypotheses that can justify a...
Andrea Censi, Daniele Calisi, Alessandro De Luca, ...
We address a new learning problem where the goal is to build a predictive model that minimizes prediction time (the time taken to make a prediction) subject to a constraint on mod...
Biswanath Panda, Mirek Riedewald, Johannes Gehrke,...
Abstract: With information infrastructures getting more and more complex, it becomes necessary to give automated support for managing the evolution of the infrastructure. If change...
In this paper, a new method for evolving simple electronic circuits is discussed, with the aim of improving the reliability and performance of basic circuit blocks. Next-generatio...
Abstract. This paper introduces a technique for region-based pose tracking without the need to explicitly compute contours. We assume a surface model of a rigid object and at least...
Christian Schmaltz, Bodo Rosenhahn, Thomas Brox, D...