photo: Edinburgh city centre - view from Calton Hill
In today's digital world, with ever increasing amounts of readily-available data comes the need to solve optimization problems of unprecedented sizes. Machine learning, compressed sensing, natural language processing, truss topology design and computational genetics are some of many prominent application domains where it is easy to formulate optimization problems with tens of thousands or millions of variables. Many modern optimization algorithms, while exhibiting great efficiency in modest dimensions, are not designed to scale to instances of this size and are hence often, unfortunately, not applicable. On the other hand, simple methods, some having been proposed decades ago, are experiencing a comeback — albeit in modern forms. This workshop aims to bring together researchers working on novel optimization algorithms capable of working in large-scale setting.
researchers, postdocs and PhD students interested in newest developments in large-scale optimization
Schedule at a Glance
Workshop: May 24, 2012
8 talks: Nesterov (Louvain), Schmidt (INRIA), Richtárik (Edinburgh), D'Aspremont (École Polytechnique), Gondzio (Edinburgh), Kočvara (Birmingham), Cartis (Edinburgh), Srebro* (TTI Chicago)
* Nati Srebro will also give a seminar talk on 'Matrix Learning: A Tale of Two Norms', on May 23rd, at 15:30, in 6206 James Clerk Maxwell Building, King's Buildings campus of U of Edinburgh (ERGO seminar series)
Trek: May 25, 2012 (morning)
Informatics Forum -> Royal Mile -> Salisbury Crags -> Arthur's Seat (and back)
Colloquium: May 25, 2012 (afternoon)
Prof. Yurii Nesterov (Universite catholique de Louvain): 'Optimization in Relative Scale'
New: Booklet (pdf)