We consider learning in a Markov decision process where we are not explicitly given a reward function, but where instead we can observe an expert demonstrating the task that we wa...
This paper addresses cost-sensitive classification in the setting where there are costs for measuring each attribute as well as costs for misclassification errors. We show how to ...
Abstract— This paper reports on our efforts to link an industrial state-of-the-art modelling tool to academic state-of-the-art analysis algorithms. In a nutshell, we enable timed...
This paper explains how Partially Observable Markov Decision Processes (POMDPs) can provide a principled mathematical framework for modelling the inherent uncertainty in spoken di...
Steve Young, Milica Gasic, Simon Keizer, Fran&cced...
An important aspect in designing a multiprotocol label switching (MPLS) network is to determine an initial topology and to adapt it to the traffic load. A topology change in an MP...
Tricha Anjali, Caterina M. Scoglio, Jaudelice Cava...