Partially observable Markov decision processes (POMDPs) provide an elegant mathematical framework for modeling complex decision and planning problems in stochastic domains in whic...
: This paper studies the asymptotic behavior of the steady-state waiting time, W∞, of the M/G/1 queue with subexponenential processing times for different combinations of traffi...
We consider the problem of approximating sliding window joins over data streams in a data stream processing system with limited resources. In our model, we deal with resource cons...
We present a new approximation method called value extrapolation for Markov processes with large or infinite state spaces. The method can be applied for calculating any performan...
When dealing with signals from complex environments, where multiple time-dependent signal signatures can interfere with each other in stochastically unpredictable ways, traditiona...