We consider Bayesian analysis of data from multivariate linear regression models whose errors have a distribution that is a scale mixture of normals. Such models are used to analy...
Star Superscalar is a task-based programming model. The programmer starts with an ordinary C program, and adds pragmas to mark functions as tasks, identifying their inputs and outp...
Abstract—We consider non-asymmetric distributed source coding (DSC) that achieves any point in the Slepian-Wolf (SW) region. We study the error propagation phenomena and propose ...
We consider semi-supervised classification when part of the available data is unlabeled. These unlabeled data can be useful for the classification problem when we make an assumpti...
As transistor dimensions continue to scale deep into the nanometer regime, silicon reliability is becoming a chief concern. At the same time, transistor counts are scaling up, ena...
Andrew DeOrio, Konstantinos Aisopos, Valeria Berta...