Most classification methods are based on the assumption that the data conforms to a stationary distribution. However, the real-world data is usually collected over certain periods...
Bayesian estimation in nonlinear stochastic dynamical systems has been addressed for a long time. Among other solutions, Particle Filtering (PF) algorithms propagate in time a Mon...
We tackle the fundamental problem of Bayesian active learning with noise, where we need to adaptively select from a number of expensive tests in order to identify an unknown hypot...
In this paper, we consider the problem of estimating the state of a dynamical system from distributed noisy measurements. Each agent constructs a local estimate based on its own m...
Data streaming management and scheduling is required by many grid computing applications, especially when the volume of data to be processed is extremely high while available stor...