Bayesian learning in undirected graphical models--computing posterior distributions over parameters and predictive quantities-is exceptionally difficult. We conjecture that for ge...
We study runtime distributions of subsumption testing. On graph data randomly sampled from two different generative models we observe a gradual growth of the tails of the distribut...
— We are given an equal number of mobile robotic agents, and distinct target locations. Each agent has simple integrator dynamics, a limited communication range, and knowledge of...
Traditionally, distributed Web servers have used two strategies for allocating files on server nodes: full replication and full distribution. While full replication provides a high...
Abstract. In the paper two notions related to local (distributed) computations are identified and discussed. The first one is the notion of reducible graphs. A graph is reducible...