Abstract. Most real-world datasets are, to a certain degree, skewed. When considered that they are also large, they become the pinnacle challenge in data analysis. More importantly...
In this paper we extend a previously introduced method for optimizing the arbitration policy employed by ServerNet routers and we evaluate the method's effect on scalability....
Vladimir Shurbanov, Dimiter R. Avresky, Robert W. ...
The stochastic approximation method is behind the solution to many important, actively-studied problems in machine learning. Despite its farreaching application, there is almost n...
The goal of sufficient dimension reduction in supervised learning is to find the lowdimensional subspace of input features that is `sufficient' for predicting output values. ...
In this paper we present a genetic algorithm applied to the problem of mission planning for Joint Suppression of Enemy Air Defenses (JSEAD) in support of air strike operations. Th...