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...
This paper discusses some aspects of fuzzy random variables obtained by propagating uncertainty in risk analysis when some input parameters are stochastic, while others are determ...
Preserving the availability and integrity of networked computing systems in the face of fast-spreading intrusions requires advances not only in detection algorithms, but also in a...
Saman A. Zonouz, Himanshu Khurana, William H. Sand...
Decentralized partially observable Markov decision process (DEC-POMDP) is an approach to model multi-robot decision making problems under uncertainty. Since it is NEXP-complete the...
Data management is becoming increasingly social. We observe a new form of information in such collaborative scenarios, where users contribute and reuse information, which resides ...