Probabilistic decision graphs (PDGs) are a representation language for probability distributions based on binary decision diagrams. PDGs can encode (context-specific) independence...
This paper addresses the problem of foreground extraction using active illumination and graph-cut optimization. Our approach starts by detecting image regions that are likely to b...
Classical rate-distortion theory requires knowledge of an elusive source distribution. Instead, we analyze rate-distortion properties of individual objects using the recently devel...
Jim Propp's rotor router model is a simple deterministic analogue of a random walk. Instead of distributing chips randomly, it serves the neighbors in a fixed order. We analy...
PageRank computes the importance of each node in a directed graph under a random surfer model governed by a teleportation parameter. Commonly denoted alpha, this parameter models ...
David F. Gleich, Paul G. Constantine, Abraham D. F...