Please join us for the latest BRIC Seminar Series, presented by:

Jieping Ye, PhD

Department of Computer Science

Arizona State University

Abstract:

Recent advances in high-throughput technologies have unleashed a torrent of biomdeical data with a large number of dimensions; biomedical investigations have become computationally more complex and more challenging. In this talk, we consider sparse methods for (1) variable selection where the structure over the features can be represented as an undirected graph or a collection of disjoint or overlapping groups, (2) multi-source data fusion with a "blockwise" data missing pattern, and (3) simultaneous construction of multiple networks. We address the computational challenge by designing novel screening strategies which scale sparse methods to large-size problems. Promising results on several biomedical applications will be presented.