In this work, we explore the idea that parameter setting of stochastic metaheuristics should be considered as a multiobjective problem. The so-called “performance fronts” pres...
Abstract. Statistical techniques for designing and analysing experiments are used to evaluate the individual and combined effects of genetic programming parameters. Three binary cl...
Choosing appropriate values for kernel parameters is one of the key problems in many kernel-based methods because the values of these parameters have significant impact on the per...
Linear inverse problems are very common in signal and image processing. Many algorithms that aim at solving such problems include unknown parameters that need tuning. In this work...
Abstract. Graph cut minimization formulates the segmentation problem as the liner combination of data and smoothness terms. The smoothness term is included in the energy formulatio...