Importance Sampling is a potentially powerful variance reduction technique to speed up simulations where the objective depends on the occurrence of rare events. However, it is cru...
For a discrete-time finite-state Markov chain, we develop an adaptive importance sampling scheme to estimate the expected total cost before hitting a set of terminal states. This s...
Abstract. Sensing mechanisms that estimate the occupancy of wireless spectrum are crucial to the success of approaches based on Dynamic Spectrum Access. In this paper, we present k...
Daniel Willkomm, Sridhar Machiraju, Jean Bolot, Ad...
Abstract. The support vector domain description is a one-class classification method that estimates the shape and extent of the distribution of a data set. This separates the data ...
Voxel based non-rigid registration of images involves finding a similarity maximising transformation that deforms a source image to the coordinate system of a target image. In orde...
Paul Aljabar, Joseph V. Hajnal, Richard G. Boyes, ...