We present a novel unsupervised learning scheme that simultaneously clusters variables of several types (e.g., documents, words and authors) based on pairwise interactions between...
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...
In this paper, we compare both discriminative and generative parameter learning on both discriminatively and generatively structured Bayesian network classifiers. We use either ma...
We study the problem of learning to accurately rank a set of objects by combining a given collection of ranking or preference functions. This problem of combining preferences aris...
Yoav Freund, Raj D. Iyer, Robert E. Schapire, Yora...
Since manual black-box testing of GUI-based APplications (GAPs) is tedious and laborious, test engineers create test scripts to automate the testing process. These test scripts in...