Bayesian networks are directed acyclic graphs that represent dependencies between variables in a probabilistic model. Many time series models, including the hidden Markov models (H...
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...
This paper introduces the problem of modeling urban transportation systems in a database where certain aspects of the data are probabilistic in nature. The transportation network ...
Joel Booth, A. Prasad Sistla, Ouri Wolfson, Isabel...
Abstract— In this paper, we present an optimization framework for target tracking with mobile robot teams. The target tracking problem is modeled as a generic semidefinite progr...
This paper investigates two fundamental characteristics of a wireless multihop network: its minimum node degree and its k?connectivity. Both topology attributes depend on the spat...