As big data algorithms find new successes in technology, business and scientific fields, researchers have started to lay the theoretical foundation for the understanding of their effectiveness. This two-day workshop provides a platform for researchers across disciplines to disseminate their recent results on topics such as large scale optimization, nonparametric and semiparametric inference, high-dimensional learning, and deep learning. It also serves as a forum to bring together academic researchers and industry scientists to promote a richer exchange of ideas and emerging opportunities.
IRSA is co-sponsoring this event with The Institute for Mathematics and its Applications (IMA). Attendees are fully supported and must apply to participate.
Visit IMA's event website to see full details and apply.
- Andrew Barron (Yale University)
- Jeff Calder (University of Minnesota, Twin Cities)
- Dennis Cook (University of Minnesota, Twin Cities)
- Runze Li (The Pennsylvania State University)
- Ian McKeague (Columbia University)