most citedLagrangian-based methods in convex optimization: prediction-correction frameworks with non-ergodic convergence rates

1 citations · 2 across the 2 of their papers we have counts for

collaborators

2 papers

math.OC2023★ 1 cited

Lagrangian-based methods in convex optimization: prediction-correction frameworks with non-ergodic convergence rates

Tao Zhang, Yong Xia, Shiru Li

Lagrangian-based methods are classical methods for solving convex optimization problems with equality constraints. We present novel prediction-correction frameworks for such method…

math.OC2022★ 1 cited

Lagrangian-based methods in convex optimization: prediction-correction frameworks with ergodic convergence rates

T. Zhang, Y. Xia, S. R. Li

We study the convergence rates of the classical Lagrangian-based methods and their variants for solving convex optimization problems with equality constraints. We present a general…