Partially observable Markov decision processes (POMDPs) allow one to model complex dynamic decision or control problems that include both action outcome uncertainty and imperfect ...
Deep belief networks are a powerful way to model complex probability distributions. However, it is difficult to learn the structure of a belief network, particularly one with hidd...
Ryan Prescott Adams, Hanna M. Wallach, Zoubin Ghah...
In the current discussion about the capacity of Bayesianism in reasoning under uncertainty, there is a conceptual and notational confusion between the explicit condition and the i...
Logical filtering is the process of updating a belief state (set of possible world states) after a sequence of executed actions and perceived observations. In general, it is intr...
Domain Name System (DNS) is the system for the mapping between easily memorizable host names and their IP addresses. Due to its criticality, security extensions to DNS have been p...