Abstract. We define a novel, basic, unsupervised learning problem learning the the lowest density homogeneous hyperplane separator of an unknown probability distribution. This task...
This paper describes a new hybrid method based on the application of the Population Training Algorithm (PTA) and linear programming (LP) for generation of schedules for drivers in...
In this paper, we consider estimating sparse inverse covariance of a Gaussian graphical model whose conditional independence is assumed to be partially known. Similarly as in [5],...
We dene the probabilistic planning problem in terms of a probability distribution over initial world states, a boolean combination of goal propositions, a probability threshold, ...
In recent years the genetic algorithm community has shown a growing interest in studying dynamic optimization problems. Several approaches have been devised. The random immigrants...