We present here an approach for applying the technique of modeling data transformation manifolds for invariant learning with kernel methods. The approach is based on building a ke...
In this paper, we propose novel blur and similarity transform (i.e. rotation, scaling and translation) invariant features for the recognition of objects in images. The features ar...
Background: Inference of evolutionary trees using the maximum likelihood principle is NP-hard. Therefore, all practical methods rely on heuristics. The topological transformations...
Abstract. This paper introduces the subject of secrecy models development by transformation, with formal validation. In an enterprise, constructing a secrecy model is a participato...
We describe a method for proving the termination of graph transformation systems. The method is based on the fact that infinite reductions must include infinite `creation chains...