In this work, we propose a simple modification of the forward-backward splitting method for
finding a zero in the sum of two monotone operators. Our method converges under the same …

In this work, we study the computational complexity of reducing the squared gradient
magnitude for smooth minimax optimization problems. First, we present algorithms with …

Convergent sequences of real numbers play a fundamental role in many different problems
in system theory, eg, in Lyapunov stability analysis, as well as in optimization theory and …

We propose a methodology for studying the performance of common splitting methods
through semidefinite programming. We prove tightness of the methodology and demonstrate …

Several new accelerated methods in minimax optimization and fixed-point iterations have
recently been discovered, and, interestingly, they rely on a mechanism distinct from …

Motivated by the training of generative adversarial networks (GANs), we study methods for
solving minimax problems with additional nonsmooth regularizers. We do so by employing …