We present a class of graphical models for directly representing the joint cumulative distribution function (CDF) of many random variables, called cumulative distribution networks...
We introduce a new type of graphical model called a `cumulative distribution network' (CDN), which expresses a joint cumulative distribution as a product of local functions. ...
In recent work, we proposed D-Trigger, a framework for tracking a global condition over a large network that allows us to detect anomalies while only collecting a very limited amo...
Ling Huang, Minos N. Garofalakis, Anthony D. Josep...
In this paper, we propose an adaptive self- stabilizing algorithm for producing a d-hop connected d-hop dominating set. In the algorithm, the set is cumulatively built with commun...
We present CRF-Gradient, a self-healing gradient algorithm that provably reconfigures in O(diameter) time. Selfhealing gradients are a frequently used building block for distribut...
Jacob Beal, Jonathan Bachrach, Daniel Vickery, Mar...