A Theory of Composition and Duality of Extremal Optimal Fixed-Point Algorithms
Abstract
In this work, we reveal a rich combinatorial structure underlying exact minimax optimal algorithms for classical nonexpansive fixed-point problems. This viewpoint unifies all extremal optimal methods and provides a systematic and practical framework for designing new algorithms via diagrams. Specifically, we study fixed-step algorithms represented by a lower triangular matrix H, and show that the set of optimal (N-1)-step algorithms has exactly (N-1)! vertices (extremal algorithms), each of which naturally corresponds to an arc diagram, a graph that encodes its convergence proof. Using these arc diagrams, we can compose, decompose, and analyze the properties of distinct optimal vertex algorithms. Furthermore, we determine when the H-dual operation, given by taking the anti-diagonal transpose of H, preserves the optimality of a vertex algorithm, and in such cases we characterize the convergence proof of the dual algorithm. Based on this machinery, we develop new optimal algorithms with quasi-anytime guarantees; that is, they admit an increasing integer sequence such that the corresponding iterates have the optimal residual guarantees, and are additionally robust to fixed-point operators that violate nonexpansiveness.
Cite
@article{arxiv.2605.02231,
title = {A Theory of Composition and Duality of Extremal Optimal Fixed-Point Algorithms},
author = {TaeHo Yoon and Benjamin Grimmer},
journal= {arXiv preprint arXiv:2605.02231},
year = {2026}
}