Composite optimization models via proximal gradient method with increasing adaptive stepsizes

We first consider the convex composite optimization models without globally Lipschitz condition imposed on the gradient of the differentiable term. The classical method which is proximal gradient will be studied with our new strategy of stepsize selection. The idea for constructing such a stepsize is motivated by the one in \cite{hoai} that used for gradient … Read more

AdaBB: Adaptive Barzilai-Borwein Method for Convex Optimization

In this paper, we propose AdaBB, an adaptive gradient method based on the Barzilai-Borwein stepsize. The algorithm is line-search-free and parameter-free, and essentially provides a convergent variant of the Barzilai-Borwein method for general unconstrained convex optimization. We analyze the ergodic convergence of the objective function value and the convergence of the iterates for solving general … Read more