The fine-tuning of the algorithms parameters, specially, in metaheuristics, is not always trivial and often is performed by ad hoc methods according to the problem under analysis. Usually, incorrect settings influence both ...

Usually, metaheuristic algorithms are adapted to a large set of problems by applying few modifications on parameters for each specific case. However, this flexibility demands a huge effort to correctly tune such parameters. ...

The fine-tuning of heuristics and metaheuristics exercises a great influence in both the solution process, as well as in the quality of results of optimization problems. The search for the best fit of these algorithms is ...

Machine Learning algorithms have been extensively researched throughout the last decade, leading to unprecedented advances in a broad range of applications, such as image classification and reconstruction, object recognition, ...

The issue of Lorentz fine-tuning in effective theories containing higher-order operators is studied. To this end, we focus on the Myers-Pospelov extension of QED with dimension-five operators in the photon sector and ...