no code implementations • 29 Jun 2023 • Yang Cai, Michael I. Jordan, Tianyi Lin, Argyris Oikonomou, Emmanouil-Vasileios Vlatakis-Gkaragkounis
Numerous applications in machine learning and data analytics can be formulated as equilibrium computation over Riemannian manifolds.
no code implementations • 10 Jun 2022 • Yang Cai, Argyris Oikonomou, Weiqiang Zheng
In our first contribution, we extend the Extra Anchored Gradient (EAG) algorithm, originally proposed by Yoon and Ryu (2021) for unconstrained min-max optimization, to constrained comonotone min-max optimization and comonotone inclusion, achieving an optimal convergence rate of $O\left(\frac{1}{T}\right)$ among all first-order methods.
no code implementations • 20 Apr 2022 • Yang Cai, Argyris Oikonomou, Weiqiang Zheng
We use the tangent residual (or a slight variation of the tangent residual) as the the potential function in our analysis of the extragradient algorithm (or the optimistic gradient descent-ascent algorithm) and prove that it is non-increasing between two consecutive iterates.
