In many prediction tasks, selecting relevant features is essential for achieving good generalization performance. Most feature selection algorithms consider all features to be a p...
Su-In Lee, Vassil Chatalbashev, David Vickrey, Dap...
We consider the task of driving a remote control car at high speeds through unstructured outdoor environments. We present an approach in which supervised learning is first used to...
In this paper, we compare both discriminative and generative parameter learning on both discriminatively and generatively structured Bayesian network classifiers. We use either ma...
This paper is concerned with the combinatorial structure of concept classes that can be learned from a small number of examples. We show that the recently introduced notion of recu...
There is a range of potential applications of Machine Learning where it would be more useful to predict the probability distribution for a variable rather than simply the most lik...
Michael Carney, Padraig Cunningham, Jim Dowling, C...