5 papers
A unified continuous-discrete framework for Nesterov acceleration: transitions between convex and strongly convex regimes
Xin He, Ya-Ping Fang
Classical Nesterov acceleration employs different choices of damping and inertial parameters in the convex and strongly convex settings, both for continuous-time dynamics and for d…
Convergence of iterates and improved rates for accelerated augmented Lagrangian methods for linearly constrained convex optimization
Xin He, Nan-Jing Huang, Yi-Bin Xiao +1
Motivated by an inertial primal-dual dynamical system with vanishing damping, we propose a class of accelerated augmented Lagrangian methods with Nesterov extrapolation parameters…
Trajectory convergence and rates for Nesterov accelerated primal-dual dynamics without Lipschitz gradient assumption
Xin He, Nan-Jing Huang, Yi-Bin Xiao +1
We consider the Nesterov accelerated primal-dual dynamical system \[ \begin{cases} \ddot{x}(t)+\dfracα{t}\dot{x}(t) +\nabla f(x(t)) +A^\top\bigl(λ(t)+θt\dotλ(t)\bigr)+βA^\top(Ax(t)…
Nesterov acceleration for strongly convex-strongly concave bilinear saddle point problems: discrete and continuous-time approaches
Xin He, Ya-Ping Fang
In this paper, we study a bilinear saddle point problem of the form , where and are - and -strongly convex f…
Accelerated linearized alternating direction method of multipliers with Nesterov extrapolation
X. He, N. J. Huang, Y. P. Fang
The alternating direction method of multipliers (ADMM) has found widespread use in solving separable convex optimization problems. In this paper, by employing Nesterov extrapolatio…