- Impact of random delays and losses in sensor networks manifests in the form of tardiness of data used for processing at the sink nodes. The age of data used by the end applicatio...
We propose a new algorithm called SCD for learning the structure of a Bayesian network. The algorithm is a kind of constraintbased algorithm. By taking advantage of variable orderi...
We consider distributed estimation of a time-dependent, random state vector based on a generally nonlinear/non-Gaussian state-space model. The current state is sensed by a serial ...
In this paper we address the problem of discretization in the context of learning Bayesian networks (BNs) from data containing both continuous and discrete variables. We describe ...
Background: Time-of-flight mass spectrometry (TOF-MS) has the potential to provide non-invasive, high-throughput screening for cancers and other serious diseases via detection of ...
Karl W. Kuschner, Dariya I. Malyarenko, William E....