In this paper we apply the recent notion of anytime universal intelligence tests to the evaluation of a popular reinforcement learning algorithm, Q-learning. We show that a general...
Feature selection for supervised learning can be greatly improved by making use of the fact that features often come in classes. For example, in gene expression data, the genes wh...
Paramveer S. Dhillon, Dean P. Foster, Lyle H. Unga...
In this paper, it is shown how to extract a hypothesis with small risk from the ensemble of hypotheses generated by an arbitrary on-line learning algorithm run on an independent an...
We approached the problem of classifying papers for the TREC 2004 Genomics Track triage task as a four step process: feature generation, feature selection, classifier training, an...
Aaron M. Cohen, Ravi Teja Bhupatiraju, William R. ...
Recently, much research has been proposed using nature inspired algorithms to perform complex machine learning tasks. Ant Colony Optimization (ACO) is one such algorithm based on s...