Particle filters (PFs) are powerful samplingbased inference/learning algorithms for dynamic Bayesian networks (DBNs). They allow us to treat, in a principled way, any type of prob...
Arnaud Doucet, Nando de Freitas, Kevin P. Murphy, ...
We design two different strategies for computing the unknown content preferences in an online social network based on a small set of nodes in the corresponding social graph for wh...
We present a state of the art read-only distributed shared memory (DSM) ray tracer capable of fully utilizing modern cluster hardware to render massive out-of-core polygonal model...
Mobile handheld devices have stringent constraints on power consumption because they run on batteries that have a limited lifetime. Conserving power to prolong battery life is of ...
In this paper, we address the problem of energy-conscious cache placement in wireless ad hoc networks. We consider a network comprising a server with an interface to the wired net...