8 citations · 14 across the 9 of their papers we have counts for
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Dual-Anchor Acceleration Is Near-Optimal for Stochastic Monotone Root-Finding
TaeHo Yoon, Nicolas Loizou
Among distinct optimal acceleration mechanisms for deterministic monotone root-finding problems and fixed-point problems, dual-anchoring has recently been shown to admit a more rob…
Anchored Extra-Proximal Methods: Optimal Higher-Order Methods for Monotone Inclusion Problems
Ruichen Jiang, TaeHo Yoon
We study the deterministic oracle complexity of finding approximate solutions to composite monotone inclusion problems, formed by the sum of a smooth single-valued monotone operato…
Polyak-Type Extragradient Methods for Monotone Root-Finding Problems
TaeHo Yoon, Sayantan Choudhury, Ezra Greenberg +1
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 c…
Direct Acceleration of Stochastic Root-Finding Without Variance Reduction and Regularization
TaeHo Yoon, Nicolas Loizou
Acceleration for deterministic root-finding problems has been extensively studied in recent years; specifically, the anchor-based, or Halpern-type methods achieve optimal convergen…
On Same-Sample and Independent-Sample Stochastic Extragradient for Monotone Variational Inequalities
TaeHo Yoon, Nicolas Loizou
We study stochastic extragradient (SEG) methods for solving monotone variational inequality problems (VIPs) over a feasible set. Although extragradient is a foundational algorithm…
H-invariance theory: A complete characterization of minimax optimal fixed-point algorithms
TaeHo Yoon, Ernest K. Ryu, Benjamin Grimmer
For nonexpansive fixed-point problems, Halpern's method with optimal parameters, its so-called H-dual algorithm, and in fact, an infinite family of algorithms containing them, all…
Optimal Acceleration for Minimax and Fixed-Point Problems is Not Unique
TaeHo Yoon, Jaeyeon Kim, Jaewook J. Suh +1
Recently, accelerated algorithms using the anchoring mechanism for minimax optimization and fixed-point problems have been proposed, and matching complexity lower bounds establish…
Accelerated Minimax Algorithms Flock Together
TaeHo Yoon, Ernest K. Ryu
Several new accelerated methods in minimax optimization and fixed-point iterations have recently been discovered, and, interestingly, they rely on a mechanism distinct from Nestero…
Accelerated Algorithms for Smooth Convex-Concave Minimax Problems with Rate on Squared Gradient Norm
TaeHo Yoon, Ernest K. Ryu
In this work, we study the computational complexity of reducing the squared gradient magnitude for smooth minimax optimization problems. First, we present algorithms with accelerat…