Abstract. AND/OR search spaces are a unifying paradigm for advanced algorithmic schemes for graphical models. The main virtue of this representation is its sensitivity to the struc...
In this paper we propose a genetic programming approach to learning stochastic models with unsymmetrical noise distributions. Most learning algorithms try to learn from noisy data...
Abstract. This paper extends and generalizes the Bayesian semisupervised segmentation algorithm [1] for oil spill detection using SAR images. In the base algorithm on which we buil...
Observing the workload on a computer system during a short (but not too short) time interval may lead to distributions that are significantly different from those that would be o...
— We consider the problem of efficiently broadcasting incremental updates to multiple terminals that contain outdated (and possibly different) initial copies of the data. This s...