Abstract. Multiple-instance learning (MIL) allows for training classifiers from ambiguously labeled data. In computer vision, this learning paradigm has been recently used in many ...
Designing efficient sorting networks has been a challenging combinatorial optimization problem since the early 1960’s. The application of evolutionary computing to this problem ...
Most applications of evolutionary algorithms (EAs) deal with static optimization problems. However, in recent years, there has been a growing interest in timevarying (dynamic) prob...
Rasmus K. Ursem, Thiemo Krink, Mikkel T. Jensen, Z...
The bandwidth minimization problem has a long history and a number of practical applications. In this paper we introduce a natural extension of bandwidth to partially ordered layo...
Abstract—Dynamic Demes is a new method for the parallelisation of evolutionary algorithms. It was derived as a combination of two other parallelisation algorithms: the master-sla...