Abstract. Interval analysis is a powerful tool which allows to design branch-and-bound algorithms able to solve many global optimization problems. In this paper we present new adap...
We present a new approach for the incorporation of shape information into a segmentation algorithm. Unlike previous approaches to the problem, our method requires no initializatio...
We investigate some approaches to solving nonconvex global optimization problems by convex nonlinear programming methods. We assume that the problem becomes convex when selected va...
Global likelihood maximization is an important aspect of many statistical analyses. Often the likelihood function is highly multi-extremal. This presents a significant challenge t...
In this paper we compare the average performance of one class of low-discrepancy quasi-Monte Carlo sequences for global optimization. Weiner measure is assumed as the probability ...