In this paper we propose a genetic programming approach to learning stochastic models with unsymmetrical noise distributions. Most learning algorithms try to learn from noisy data...
Computing reliable gene expression levels from microarray experiments is a sophisticated process with many potential pitfalls. Quality control is one of the most important steps i...
Many challenges remain in the development of tactical planning systems that will enable automated, cooperative replanning of routes and mission assignments for multiple unmanned gr...
Talib S. Hussain, David J. Montana, Gordon Vidaver
This paper presents a system that extracts 109 musical features from symbolic recordings (MIDI, in this case) and uses them to classify the recordings by genre. The features used ...
We present an application of inductive concept learning and interactive visualization techniques to a large-scale commercial data mining project. This paper focuses on design and c...
William H. Hsu, Michael Welge, Thomas Redman, Davi...