Abstract--The paper proposes a model which allows integration of services published by independent providers into scientific or business workflows. Optimization algorithms are prop...
Abstract--Feature selection is an important challenge in machine learning. Unfortunately, most methods for automating feature selection are designed for supervised learning tasks a...
In the Software/Hardware Engineering model-driven design methodology, preservation of real-time system properties can be guaranteed in the model synthesis up to a small time-deviat...
Abstract--This paper examines the initial parallel implementation of SCATTER, a computationally intensive inelastic neutron scattering routine with polycrystalline averaging capabi...
In this paper, we propose a model named Logical Markov Decision Processes with Negation for Relational Reinforcement Learning for applying Reinforcement Learning algorithms on the ...