We develop a hierarchical distributed production planning and control methodology, called DISCS, for a large and unstable semiconductor manufacturing process. The upper layer of D...
This paper presents a new functional parallel language: Minimally Synchronous Parallel ML. The execution time can then be estimated and dead-locks and indeterminism are avoided. I...
We address the problem of learning structure in nonlinear Markov networks with continuous variables. This can be viewed as non-Gaussian multidimensional density estimation exploit...
In this paper, we develop algorithms for robust linear regression by leveraging the connection between the problems of robust regression and sparse signal recovery. We explicitly ...
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...