Abstract. Capturing regularities in high-dimensional data is an important problem in machine learning and signal processing. Here we present a statistical model that learns a nonli...
Background: Data from metabolomic studies are typically complex and high-dimensional. Principal component analysis (PCA) is currently the most widely used statistical technique fo...
Gift Nyamundanda, Lorraine Brennan, Isobel Claire ...
For a grid middleware to perform resource allocation, prediction models are needed, which can determine how long an application will take for completion on a particular platform o...
Secure multiparty computation allows parties to jointly compute a function of their private inputs without revealing anything but the output. Theoretical results [2] provide a gen...
Developments in whole genome biotechnology have stimulated statistical focus on prediction methods. We review here methodology for classifying patients into survival risk groups a...
Richard M. Simon, Jyothi Subramanian, Ming-Chung L...