Primal and dual variables decomposition methods in convex optimization
Event details
| Date | 15.04.2016 |
| Hour | 10:15 › 11:15 |
| Speaker |
Amir Beck, Technion Bio: Amir Beck is a Professor in the Department of Industrial Engineering at The Technion—Israel Institute of Technology. He has published numerous papers, has given invited lectures at international conferences, and was awarded the Salomon Simon Mani Award for Excellence in Teaching and the Henry Taub Research Prize. His research interests are in continuous optimization, including theory, algorithmic analysis, and applications. He is an associate editor of Mathematics of Operations Research, the Journal of Optimization Theory and Applications, Optimization Methods and Software and an area editor for optimization in Operations Research. His research has been supported by various funding agencies, including the Israel Science Foundation, the German-Israeli Foundation, the Binational US-Israel foundation, the Israeli Science and Energy Ministries and the European community. |
| Location | |
| Category | Conferences - Seminars |
In recent years, due to the “big data” revolution, large-scale and even huge-scale applications have started to emerge, and consequently the need for new, fast and reliable decomposition methods has become evident. We consider a class of block descent methods that involve the solution of many simple optimization subproblems of small dimension in place of the original problem. Rates of convergence of different variants will be presented and the dual functional form will be explored. The effectiveness of the methods will be illustrated on several scientific applications.
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