This paper studies the convergence rate of a second-order dynamical system associated
with a nonsmooth bilinearly coupled convex-concave saddle point problem, as well as the …

The choice of the stepsize in first-order convex optimization is typically based on the
smoothness constant and plays a crucial role in the performance of algorithms. Recently …

The class of convex–concave bilinear saddle point problems encompasses many important
convex optimization models arising in a wide array of applications. The most of existing …

In this paper, we design an inertial accelerated primal–dual algorithm to address the convex–
concave saddle point problem, which is formulated as min x max yf (x)+< K x, y>− g (y) …

In this paper, we design first-order primal-dual algorithms to address the convex-concave
saddle point problem, which is formulated as $\min_ {x}\max_ {y} f (x)+\langle Kx, y\rangle-g …

Accounting for climate transition risks is one of the most important challenges in the
transition to a low-carbon economy. Banks are encouraged to align their investment …

In this paper, we aim to solve a convex-concave min–max optimization problem, where the
convex-concave coupling function is nonsmooth in both variables. We propose a simple …

Asen L. Dontchev was born on June 19, 1948, in Pleven, Bulgaria, where he completed his
high school education. Recognition of his mathematical talent inspired him to study at the …

Minimax optimization problems are an important class of optimization problems arising from
modern machine learning and traditional research areas. While there have been many …

Training neural networks that require adversarial optimization, such as generative
adversarial networks (GANs) and unsupervised domain adaptations (UDAs), suffers from …