Talks
Fall 2013
![](https://old.simons.berkeley.edu/sites/default/files/styles/workshop_main/public/big_data_recreate.jpg?itok=XckznfAb)
A Dual Approach to Sparse Optimization
Wednesday, September 18th, 2013, 2:00 pm–2:45 pm
A feature common to many sparse optimization problems is that the number of variables may be significantly larger than the number of constraints—e.g., the standard matrix-lifting approach for binary optimization results in a problem where the number of variables is quadratic in the number of constraints. We consider a duality framework applicable to a wide range of nonsmooth sparse optimization problems that allows us to leverage the relatively small number of constraints. Preliminary numerical results illustrate our approach and its flexibility.