We investigate methods for planning in a Markov Decision Process where the cost function is chosen by an adversary after we fix our policy. As a running example, we consider a rob...
H. Brendan McMahan, Geoffrey J. Gordon, Avrim Blum
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...
Parallel MR imaging is an effective approach to reduce MR image acquisition time. Non-uniform subsampling allows one to tailor the subsampling scheme for improved image quality at...
William Scott Hoge, Misha Elena Kilmer, Steven Hak...
We propose a new Bayesian, stochastic tracking algorithm for the segmentation of blood vessels from 3D medical image data. Inspired by the recent developments in particle filterin...
David Lesage, Elsa D. Angelini, Isabelle Bloch, Ga...
An important issue arising from Peer-to-Peer applications is how to accurately and efficiently retrieve a set of K best matching data objects from different sources while minimizi...