Multiagent probabilistic reasoning with multiply sectioned Bayesian networks requires interfacing agent subnets (the modeling task) subject to a set of conditions. To specify the ...
Large-scale scientific computing applications frequently make use of closely-coupled distributed parallel components. The performance of such applications is therefore dependent o...
In this paper, we present a novel technique for modeling the posterior probability estimates obtained from a neural network directly in the HMM framework using the Dirichlet Mixtu...
Balakrishnan Varadarajan, Garimella S. V. S. Sivar...
We present a task model for adaptive real-time tasks in which a task's execution rate requirements are allowed to change at any time. The model, variable rate execution (VRE)...
In the traditional mixture of Gaussians background model, the generating process of each pixel is modeled as a mixture of Gaussians over color. Unfortunately, this model performs ...