The dramatic increase in the number of mobile subscribers has put a significant resource and service provisioning strain on current cellular networks in particular in terms of mu...
We introduce a framework for syntactic parsing with latent variables based on a form of dynamic Sigmoid Belief Networks called Incremental Sigmoid Belief Networks. We demonstrate ...
This paper introduces a generic theoretical framework for predictive learning, and relates it to data-driven and learning applications in earth and environmental sciences. The iss...
Vladimir Cherkassky, Vladimir M. Krasnopolsky, Dim...
— We present an analytic and geometric view of the sample mean of graphs. The theoretical framework yields efficient subgradient methods for approximating a structural mean and ...
This paper starting from the very first principle presents a derivation of an equation estimating of the final prediction error for a neural network under the recursive least squa...