in recent years, soft computing methods have generated a large research interest. the synthesis of the fuzzy logic and the evolutionary algorithms is one of these methods. a particular evolutionary algorithm (ea) is differential evolution (de). as for any ea, de algorithm also requires parameters tuning to achieve desirable performance. in this paper tuning the perturbation factor vector of de ...

This paper is concerned with automated tuning of parameters of algorithms to handle heterogeneous and large instances. We propose an automated parameter tuning framework with the capability to provide instance-specific parameter configurations. We report preliminary results on the Quadratic Assignment Problem (QAP) and show that our framework provides a significant improvement on solutions qual...

The tuning parameter selection strategy for penalized estimation is crucial to identify a model that both interpretable and predictive. However, popular strategies (e.g., minimizing average squared prediction error via cross-validation) tend select models with more predictors than necessary. A simple yet powerful cross validation proposed which based on maximizing the correlation between observ...