Graph-based methods for semi-supervised learning have recently been shown to be promising for combining labeled and unlabeled data in classification problems. However, inference f...
This paper deals with the adaptive variance scaling issue in continuous Estimation of Distribution Algorithms. A phenomenon is discovered that current adaptive variance scaling me...
In this paper we describe a new approach for the well known problem in bioinformatics: Multiple Sequence Alignment (MSA). MSA is fundamental task as it represents an essential pla...
Case-based approaches are employed within a multitude of application areas one of which is the prediction of dynamic behaviour. Given a situation the possible development after a ...
In this paper we propose a unified architectural support that can be used flexibly for either soft-error protection or software bug detection. Our approach is based on dynamically...