10 citations · 16 across the 4 of their papers we have counts for
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math.OC2022★ 1 cited
A universal accelerated primal-dual method for convex optimization problems
Hao Luo
This work presents a universal accelerated first-order primal-dual method for affinely constrained convex optimization problems. It can handle both Lipschitz and Hölder gradients b…
math.OC2021★ 5 cited
A Unified Convergence Analysis of First Order Convex Optimization Methods via Strong Lyapunov Functions
Long Chen, Hao Luo
We present a unified convergence analysis for first order convex optimization methods using the concept of strong Lyapunov conditions. Combining this with suitable time scaling fac…
math.OC2019★ 10 cited
First order optimization methods based on Hessian-driven Nesterov accelerated gradient flow
Long Chen, Hao Luo
A novel dynamical inertial Newton system, which is called Hessian-driven Nesterov accelerated gradient (H-NAG) flow is proposed. Convergence of the continuous trajectory are establ…