We are working on a project aimed at building next generation analyst support tools that focus analysts’ attention on the most critical and novel information found within the da...
The desire to predict power generation at a given point in time is essential to power scheduling, energy trading, and availability modeling. The research conducted within is conce...
Naive Bayes is one of the most efficient and effective inductive learning algorithms for machine learning and data mining. Its competitive performance in classification is surpris...
In this paper the distributed Constraint Satisfaction Ant Algorithm (CSAA) framework is presented. It uses an ant-based system for the distributed solving of constraint satisfacti...
We present results from experiments in using several pitch representations for jazz-oriented musical tasks performed by a recurrent neural network. We have run experiments with se...