We describe a method for predicting query difficulty in a precision-oriented web search task. Our approach uses visual features from retrieved surrogate document representations (...
Eric C. Jensen, Steven M. Beitzel, David A. Grossm...
The Relevance Vector Machine (RVM) is a sparse approximate Bayesian kernel method. It provides full predictive distributions for test cases. However, the predictive uncertainties ...
This paper presents an investigation into the combination of different classifiers for toxicity prediction. These classification methods involved in generating classifiers for comb...
Abstract. Feature subset selection is an important subject when training classifiers in Machine Learning (ML) problems. Too many input features in a ML problem may lead to the so-...
We present a simple statistical model of molecular function evolution to predict protein function. The model description encodes general knowledge of how molecular function evolve...
Barbara E. Engelhardt, Michael I. Jordan, Steven E...