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...
Many optimization techniques have been adopted for efficient job scheduling in grid computing, such as: genetic algorithms, simulated annealing and stochastic methods. Such techni...
Renato Porfirio Ishii, Rodrigo Fernandes de Mello,...
We consider the problem of verifying reachability properties of stochastic real-time systems modeled as generalized semi-Markov processes (GSMPs). The standard simulation-based tec...
Abstract. Wireless sensor networks (WSNs) are comprised of energy constrained nodes. This limitation has led to the crucial need for energy-aware protocols to produce an efficient ...
Xiaoling Wu, Jinsung Cho, Brian J. d'Auriol, Sungy...
The black box algorithm for separating the numerator from the denominator of a multivariate rational function can be combined with sparse multivariate polynomial interpolation alg...