Background: Motif finding algorithms have developed in their ability to use computationally efficient methods to detect patterns in biological sequences. However the posterior cla...
Ana C. Casimiro, Susana Vinga, Ana T. Freitas, Arl...
In recent years, there have been some interesting studies on predictive modeling in data streams. However, most such studies assume relatively balanced and stable data streams but...
It is becoming increasingly important to learn from a partially-observed random matrix and predict its missing elements. We assume that the entire matrix is a single sample drawn ...
XCS is a flexible system for data mining due to its ability to deal with environmental changes, learn online with little prior knowledge and evolve accurate and maximally general...
In this paper, we formulate the shape localization problem in the Bayesian framework. In the learning stage, we propose the Constrained RankBoost approach to model the likelihood ...