We propose a new model for the probabilistic estimation of continuous state variables from a sequence of observations, such as tracking the position of an object in video. This ma...
Abstract. Ensemble learning is a powerful learning approach that combines multiple classifiers to improve prediction accuracy. An important decision while using an ensemble of cla...
We study the problem of classifying images into a given, pre-determined taxonomy. The task can be elegantly translated into the structured learning framework. Structured learning, ...
We propose a rule-based approach for transforming B abstract machines into UML diagrams. We believe that important insight into the structure underlying a B model can be gained by...
This paper describes Embra, a simulator for the processors, caches, and memory systems of uniprocessors and cache-coherent multiprocessors. When running as part of the SimOS simul...