Inverse Reinforcement Learning (IRL) is the problem of learning the reward function underlying a Markov Decision Process given the dynamics of the system and the behaviour of an e...
Generally, ontology learning and population is applied as a semi-automatic approach to knowledge acquisition in natural language understanding systems. That means, after the ontol...
—Workload characterisation and generation is becoming an increasingly important area as hardware and application complexities continue to advance. In this paper, we introduce a c...
Diffusion processes are a family of continuous-time continuous-state stochastic processes that are in general only partially observed. The joint estimation of the forcing paramete...
WCET analysis models for superscalar out-of-order CPUs generally need to be pessimistic in order to account for a wide range of possible dynamic behavior. CPU hardware modificatio...