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...
In technical chemistry, systems biology and biotechnology, the construction of predictive models has become an essential step in process design and product optimization. Accurate ...
In this paper we show that complex (scale-free) network topologies naturally emerge from hyperbolic metric spaces. The hyperbolic geometry can be used to facilitate maximally efï¬...
Fragkiskos Papadopoulos, Dmitri V. Krioukov, Mari&...
Abstract. In the community of sentiment analysis, supervised learning techniques have been shown to perform very well. When transferred to another domain, however, a supervised sen...
Why is probabilistic roadmap (PRM) planning probabilistic? How does the probability measure used for sampling a robot’s conï¬guration space affect the performance of a PRM plan...