Indicator-based algorithms have become a very popular approach to solve multi-objective optimization problems. In this paper, we contribute to the theoretical understanding of alg...
We have developed methods for segmentation and tracking of cells in time-lapse phase-contrast microscopy images. Our multi-object Bayesian algorithm detects and tracks large num...
David House, Matthew Walker, Zheng Wu, Joyce Wong,...
We present two novel perturbation-based linkage learning algorithms that extend LINC [5]; a version of LINC optimised for decomposition tasks (oLINC) and a hierarchical version of...
In recent years, there is an increasing interest in the Semantic Web and the relevant technologies, which can have a significant impact in the context of information and knowledge...
Barbara Bazzanella, Themis Palpanas, Heiko Stoerme...
Metaheuristics have often been shown to be effective for difficult combinatorial optimization problems. The reason for that, however, remains unclear. A framework for a theory of ...