Fast and flexible message demultiplexing are well-established goals in the networking community [1, 18, 22]. Currently, however, network architects have had to sacrifice one for t...
We propose an analytic moment-based filter for nonlinear stochastic dynamic systems modeled by Gaussian processes. Exact expressions for the expected value and the covariance matr...
Marc Peter Deisenroth, Marco F. Huber, Uwe D. Hane...
One problem encountered while monitoring gigabit networks, is the need to filter only those packets that are interesting for a given task while ignoring the others. Popular packet...
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 study the scalable management of XML data in P2P networks based on distributed hash tables (DHTs). We identify performance limitations in this context, and propose an array of t...