Abstract— This paper is concerned with control applications over lossy data networks. Sensor data is transmitted to an estimation-control unit over a network, and control command...
Emanuele Garone, Bruno Sinopoli, Alessandro Casavo...
We discuss the problem of overfitting of probabilistic neural networks in the framework of statistical pattern recognition. The probabilistic approach to neural networks provides a...
The (M, W)-controller, originally studied by Afek, Awerbuch, Plotkin, and Saks, is a basic distributed tool that an abstraction for managing the consumption of a global resource i...
While quantitative probabilistic networks (QPNs) allow the expert to state influences between nodes in the network as influence signs, rather than conditional probabilities, infer...
While known algorithms for sensitivity analysis and parameter tuning in probabilistic networks have a running time that is exponential in the size of the network, the exact comput...