We introduce a new causal hierarchical belief network for image segmentation. Contrary to classical tree structured (or pyramidal) models, the factor graph of the network contains...
Large-scale sensor network applications require in-network processing and data fusion to compute statistically relevant summaries of the sensed measurements. This paper studies di...
Jeremy Schiff, Dominic Antonelli, Alexandros G. Di...
We present fault localization techniques suitable for diagnosing end-to-end service problems in communication systems with complex topologies. We refine a layered system model th...
Abstract— Real-world robotic environments are highly structured. The scalability of planning and reasoning methods to cope with complex problems in such environments crucially de...
In probabilistics, reasoning at optimum entropy (ME-reasoning) has proved to be a most sound and consistent method for inference. This paper investigates its properties in the fram...