Abstract. Algorithm selection is typically based on models of algorithm performance learned during a separate offline training sequence, which can be prohibitively expensive. In r...
The number of states in discrete event systems can increase exponentially with respect to the size of the system. A way to face this state explosion problem consists of relaxing t...
The BMI Eigenvalue Problem is one of optimization problems and is to minimize the greatest eigenvalue of a bilinear matrix function. This paper proposes a parallel algorithm to co...
Many data mining applications involve the task of building a model for predictive classification. The goal of such a model is to classify examples (records or data instances) into...
Elon S. Correa, Alex Alves Freitas, Colin G. Johns...
The integration of multiple predictors promises higher prediction accuracy than the accuracy that can be obtained with a single predictor. The challenge is how to select the best ...