5 papers
On Convergence of Regularized Barzilai-Borwein Method
Xin Xu
The regularized Barzilai-Borwein (RBB) method represents a promising gradient-based optimization algorithm. In this paper, by splitting the gradient into two parts and analyzing th…
On Convergence and Stability of Two Extended BB-like Step Sizes
Xin Xu
The Barzilai-Borwein (BB) step sizes have a profound impact on gradient descent methods. In this work, we propose two new gradient step sizes: one longer than the original long BB…
An adaptive ADMM with regularized spectral penalty for sparse portfolio selection
Xin Xu
The mean-variance (MV) model is the core of modern portfolio theory. Nevertheless, it suffers from the over-fitting problem due to the estimation errors of model parameters. We con…
A Parameterized Barzilai-Borwein Method via Interpolated Least Squares
Xin Xu
The Barzilai-Borwein (BB) method is an effective gradient descent algorithm for solving unconstrained optimization problems. Based on the observation of two classical BB step sizes…
A Trust Region Method with Regularized Barzilai-Borwein Step-Size for Large-Scale Unconstrained Optimization
Xin Xu, Congpei An
We develop a Trust Region method with Regularized Barzilai-Borwein step-size obtained in a previous paper for solving large-scale unconstrained optimization problems. Simultaneousl…