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...
Graph-theoretical representations for sets of probability measures (credal networks) generally display high complexity, and approximate inference seems to be a natural solution fo...
The navigation of structural dependencies (e.g., method invocations) when a developer performs a change task is an effective strategy in program investigation. Several existing ap...
Abstract. This paper gives an overview of the KeY approach and highlights the main features of the KeY system. KeY is an approach (and a system) for the deductive verification of ...
In this paper we propose a power penalty approach to linear complementarity problems (LCP) in a finite dimensional space. This approach is based on approximating the LCP by a nonl...