Bayesian learning in undirected graphical models--computing posterior distributions over parameters and predictive quantities-is exceptionally difficult. We conjecture that for ge...
An analytical model is developed to solve the power-rate assignment problem for multi-rate CDMA systems and calculate the probability density function (PDF) for the downlink traffi...
We give a practical and provably good Monte Carlo algorithm for approximating center points. Let P be a set of n points in IRd . A point c ∈ IRd is a β-center point of P if eve...
Kenneth L. Clarkson, David Eppstein, Gary L. Mille...
This paper presents a new deterministic approximation technique in Bayesian networks. This method, "Expectation Propagation," unifies two previous techniques: assumed-de...
We consider a distributed system where each node keeps a local count for items (similar to elections where nodes are ballot boxes and items are candidates). A top-k query in such ...