Optimization problems are typically addressed by purely automatic approaches. For multi-objective problems, however, a single best solution often does not exist. In this case, it ...
Rigorous runtime analyses of evolutionary algorithms (EAs) mainly investigate algorithms that use elitist selection methods. Two algorithms commonly studied are Randomized Local S...
Edda Happ, Daniel Johannsen, Christian Klein, Fran...
We present an evaluation strategy for clock synchronization algorithms. It is based on a combination of measured traces, which provide for realistic performance estimation, and of...
We study the problem of quantization of discrete probability distributions, arising in universal coding, as well as other applications. We show, that in many situations this probl...
The aim of this paper is to study the use of Evolutionary Multiobjective Techniques to improve the performance of Neural Networks (NN). In particular, we will focus on classificati...