Seminar | November 13 | 3-4 p.m. | Cory Hall, 540 Cory
Lieven Vandenberghe, UCLA
The talk will be on primal-dual first order methods derived from the Douglas-Rachford operator splitting algorithm. We will start with some applications to image deblurring problems
that illustrate the versatility of the Douglas-Rachford method for primal-dual decomposition in large scale optimization. The second part of the talk will be concerned with the important primal-dual hybrid gradient (PDHG) method. This method is widely used in image processing, computer vision, and machine learning. We will show how the PDHG method can be derived from the Douglas-Rachford splitting method, and discuss some implications of this derivation for the convergence analysis and extensions of PDHG.
(Joint work with Daniel O'Connor.)