8 papers
On the convergence rate of the boosted Difference-of-Convex Algorithm (DCA)
Hadi Abbaszadehpeivasti, Etienne de Klerk, Adrien Taylor
The difference-of-convex algorithm (DCA) is a well-established nonlinear programming technique that solves successive convex optimization problems. These sub-problems are obtained…
On the convergence rate of the Douglas-Rachford splitting algorithm
Hadi Abbaszadehpeivasti, Moslem Zamani
This work is concerned with the convergence rate analysis of the Douglas-Rachford splitting (DRS) method for finding a zero of the sum of two maximally monotone operators. We obtai…
Convergence rate analysis of randomized and cyclic coordinate descent for convex optimization through semidefinite programming
Hadi Abbaszadehpeivasti, Etienne de Klerk, Moslem Zamani
In this paper, we study randomized and cyclic coordinate descent for convex unconstrained optimization problems. We improve the known convergence rates in some cases by using the n…
Convergence rate analysis of the gradient descent-ascent method for convex-concave saddle-point problems
Moslem Zamani, Hadi Abbaszadehpeivasti, Etienne de Klerk
In this paper, we study the gradient descent-ascent method for convex-concave saddle-point problems. We derive a new non-asymptotic global convergence rate in terms of distance to…
The exact worst-case convergence rate of the alternating direction method of multipliers
Moslem Zamani, Hadi Abbaszadehpeivasti, Etienne de Klerk
Recently, semidefinite programming performance estimation has been employed as a strong tool for the worst-case performance analysis of first order methods. In this paper, we deriv…
Conditions for linear convergence of the gradient method for non-convex optimization
Hadi Abbaszadehpeivasti, Etienne de Klerk, Moslem Zamani
In this paper, we derive a new linear convergence rate for the gradient method with fixed step lengths for non-convex smooth optimization problems satisfying the Polyak-Lojasiewicz…