The problem of model selection for support vector machines (SVMs) is considered. We propose an evolutionary approach to determine multiple SVM hyperparameters: The covariance matr...
—A promising method of automating management tasks in computing systems is to formulate them as control or optimization problems in terms of performance metrics. For an online op...
We present a method for parameter learning in relational Bayesian networks (RBNs). Our approach consists of compiling the RBN model into a computation graph for the likelihood fun...
In order to achieve the best application-level Quality-of-Service (QoS), multimedia applications need to be dynamically tuned and reconfigured to adapt to fluctuating computing an...
The performance of a Multiobjective Evolutionary Algorithm (MOEA) is crucially dependent on the parameter setting of the operators. The most desired control of such parameters pre...