When constructing a Bayesian network, it can be advantageous to employ structural learning algorithms to combine knowledge captured in databases with prior information provided by...
Learning data representations is a fundamental challenge in modeling neural processes and plays an important role in applications such as object recognition. In multi-stage Optima...
In this paper we present a scalable and distributed access structure for similarity search in metric spaces. The approach is based on the Content– addressable Network (CAN) parad...
Production of a large-scale software system involves quite a few software components. It is very common to develop such software components in a distributed environment consisting...
Encouraging exploration, typically by preserving the diversity within the population, is one of the most common method to improve the behavior of evolutionary algorithms with dece...