The digitalization of objects from the real world is of great importance, e. g., in many multimedia applications, in 3D computer graphics, and in industrial measurement. In partic...
Christian Teutsch, Erik Trostmann, Michael Weber, ...
We study decision making in environments where the reward is only partially observed, but can be modeled as a function of an action and an observed context. This setting, known as...
Partially Observable Markov Decision Processes have been studied widely as a model for decision making under uncertainty, and a number of methods have been developed to find the s...
Recently developed dual techniques allow us to evaluate a given sub-optimal dynamic portfolio policy by using the policy to construct an upper bound on the optimal value function....
The evaluation of privacy-preserving techniques for LBS is often based on simulations of mostly random user movements that only partially capture real deployment scenarios. We clai...