Abstract. Modern description logic (DL) reasoners are known to be less efficient for DLs with inverse roles. The current loss of performance is largely due to the missing applicabi...
In this paper, we consider Markov Decision Processes (MDPs) with error states. Error states are those states entering which is undesirable or dangerous. We define the risk with re...
The class of algorithms for approximating reasoning tasks presented in this paper is based on approximating the general bucket elimination framework. The algorithms have adjustabl...
We present an interactive application that enables users to improve the visual aesthetics of their digital photographs using spatial recomposition. Unlike earlier work that focuse...
We develop logarithmic approximation algorithms for extremely general formulations of multiprocessor multiinterval offline task scheduling to minimize power usage. Here each proce...