Optimal error bounds for nonexpansive fixed-point iterations in normed spaces
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Abstract (arXiv)
This paper investigates optimal error bounds and convergence rates for general Mann iterations for computing fixed-points of non-expansive maps. We look for iterations that achieve the smallest fixed-point residual after n steps, by minimizing a worst-case bound |xn-Txn|≤ Rn derived from a nested family of optimal transport problems. We prove that this bound is tight so that minimizing Rn yields optimal iterations. Inspired from numerical results we identify iterations that attain the rate Rn=O(1/n), which we also show to be the best possible. In particular, we prove that the classical Halpern iteration achieves this optimal rate for several alternative stepsizes, and we determine analytically the optimal stepsizes that attain the smallest worst-case residuals at every step n, with a tight bound Rn≈frac4n+4. We also determine the optimal Halpern stepsizes for affine non-expansive maps, for which we get exactly Rn=frac1n+1. Finally, we show that the best rate for the classical Krasnosel'skiui-Mann iteration is Omega(1/√n), and present numerical evidence suggesting that even extended variants cannot reach a faster rate.
Key facts. Cited by 12 papers in the map (data through 7 Oct 2026). First posted on arXiv 24 Aug 2021.
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Citing papers per year: 2022: 1; 2023: 1; 2024: 1; 2025: 3; 2026: 6.
12 papers.
- 2022Stochastic Halpern Iteration with Variance Reduction for Stochastic Monotone Inclusionscited by 17
- 2024Stochastic Halpern iteration in normed spaces and applications to reinforcement learningcited by 11
- 2023Accelerating Value Iteration with Anchoringcited by 10
- 2026Solving Stochastic Fixed-Point Equations with High Probabilitycited by 3
- 2025Model-Free Robust Average-Reward Reinforcement Learning with Sample Complexity Analysiscited by 2
- 2025Faster Fixed-Point Methods for Multichain MDPscited by 2
- 2025Finite-Time Bounds for Average-Reward Fitted Q-Iterationcited by 1
- 2026A Unifying View of Anchoring via Operator-Side Tikhonov Regularizationcited by 0
- 2026Oracle Complexity of Stochastic Fixed-Point Equations with Nonexpansive Mapscited by 0
- 2026Polyak-Type Extragradient Methods for Monotone Root-Finding Problemscited by 0
- 2026Stochastic Inertial Krasnosel'skii-Mann Iteration Achieves Near-Optimal Sample Complexitycited by 0
- 2026Dual-Anchor Acceleration Is Near-Optimal for Stochastic Monotone Root-Findingcited by 0
- 2026Dual-Anchor Acceleration Is Near-Optimal for Stochastic Monotone Root-Finding28 Sep 2026
- 2026Stochastic Inertial Krasnosel'skii-Mann Iteration Achieves Near-Optimal Sample Complexity22 Sep 2026
- 2026Polyak-Type Extragradient Methods for Monotone Root-Finding Problems22 Sep 2026
- 2026Oracle Complexity of Stochastic Fixed-Point Equations with Nonexpansive Maps8 Sep 2026
- 2026Solving Stochastic Fixed-Point Equations with High Probability10 Jul 2026
- 2026A Unifying View of Anchoring via Operator-Side Tikhonov Regularization29 May 2026
- 2025Finite-Time Bounds for Average-Reward Fitted Q-Iteration20 Oct 2025
- 2025Faster Fixed-Point Methods for Multichain MDPs26 Jun 2025
- 2025Model-Free Robust Average-Reward Reinforcement Learning with Sample Complexity Analysis18 May 2025
- 2024Stochastic Halpern iteration in normed spaces and applications to reinforcement learning19 Mar 2024
- 2023Accelerating Value Iteration with Anchoring26 May 2023
- 2022Stochastic Halpern Iteration with Variance Reduction for Stochastic Monotone Inclusions17 Mar 2022