Tin mới

Tên báo cáo: "Fast Augmented Lagrangian Method in continuous and discrete setting"
Người trình bày: Nguyễn Đăng Khoa, đang làm postdoc tại University of Vienna.
Nội dung báo cáo:
We approach the minimization of a continuously differentiable convex
function under linear equality constraints by a second-order dynamical
system with asymptotically vanishing damping term. The system is
formulated in terms of the augmented Lagrangian associated to the
minimization problem. We show fast convergence of the primal-dual gap,
the feasibility measure, and the objective function value along the
generated trajectories. In case the objective function has Lipschitz
continuous gradient, we show that the primal-dual trajectory
asymptotically weakly converges to a primal-dual optimal solution of the
underlying minimization problem. The proposed inertial algorithm results
from the discretization of the second-order primal-dual dynamical
Địa điểm: Phòng F207. Sáng 9h ngày 23/9/2022.