The optimization problems occurring in nonlinear regression normally cannot be proven unimodal. In the present paper applicability of global optimization algorithms to this problem...
Unsupervised learning methods often involve summarizing the data using a small number of parameters. In certain domains, only a small subset of the available data is relevant for ...
A learning-based face hallucination method is proposed in this paper for the reconstruction of a high-resolution face image from a low-resolution observation based on a set of high...
In this paper we address the problem of global real-time periodic scheduling on heterogeneous multiprocessor platforms. We give a solution based on a constraint satisfaction proble...
Genetic Algorithms are very powerful search methods that are used in different optimization problems. Parallel versions of genetic algorithms are easily implemented and usually in...