An approach to semi-supervised learning is proposed that is based on a Gaussian random field model. Labeled and unlabeled data are represented as vertices in a weighted graph, wit...
Abstract –In this paper, a variational message passing framework is proposed for Markov random fields, which is computationally more efficient and admits wider applicability comp...
We present a large-system performance analysis of blind and group-blind multiuser detection methods. In these methods, the receivers are estimated based on the received signal samp...
— It is a commonly held belief that IPv6 provides greater security against random-scanning worms by virtue of a very sparse address space. We show that an intelligent worm can ex...
We propose a principled framework for recursively segmenting deformable objects across a sequence of frames. We demonstrate the usefulness of this method on left ventricular segmen...