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The Anchored Extra-Proximal (AEP) framework is introduced, which combines an anchored extrapolation step with an inexact anchored proximal update satisfying a relative-error condition to recover the composite Fast Extragradient method in the first-order setting.
We study Polyak-type step-size selection for extragradient methods for solving deterministic and stochastic monotone root-finding problems. We show that the known projection-type correction for deterministic extragradient arises from minimizing an upper bound on the distance to a solution, paralleling the classical Pol...
We study stochastic extragradient (SEG) methods for solving monotone variational inequality problems (VIPs) over a feasible set. Although extragradient is a foundational algorithm for VIPs and its deterministic convergence theory is well developed, its stochastic counterpart remains less understood. Most existing analy...
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