mlsanityData to 14 Oct 2026

A Unifying View of Anchoring via Operator-Side Tikhonov Regularization

arXiv 2605.30905 ↗First posted 29 May 2026math.OC cs.LGcited by 0

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Abstract (arXiv)

Anchored fixed point and monotone equation methods, including Halpern iteration, extra anchored gradient, and their relatives, add a vanishing pull toward a reference point to obtain last-iterate guarantees. Existing anchored variants often achieve sharp last-iterate guarantees, but from the update-level perspective the placement of the anchor can be algorithm-specific and conceptually opaque. We show that anchoring admits a single operator-side construction: regularize the operator queried by the base method with a vanishing Tikhonov term, then run the unmodified base method. Applied to the Picard iteration, this recipe reproduces the Halpern iteration; applied to the forward step, extragradient (EG), and past extragradient (PEG, also known as Popov's method), it yields three variants whose anchor placements inherit the base method's query pattern. The forward-step instantiation gives a new residual convergence guarantee, while the EG and PEG instantiations give new regularized variants. The four analyses share a residual recurrence, recovering the O(1/k) Halpern residual-norm convergence rate, giving O(1/√k) for the regularized forward step, and giving O(1/k) for the regularized EG and PEG variants in the unconstrained monotone Lipschitz setting.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 17 of its 38 references that are in the map. First posted on arXiv 29 May 2026.

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17 of 38 references.

References · 17

  1. 2021Accelerated Algorithms for Smooth Convex-Concave Minimax Problems with O(1/k2) Rate on Squared Gradient Normcited by 73
  2. 2017A First Order Method for Solving Convex Bi-Level Optimization Problemscited by 67
  3. 2021Fast Extra Gradient Methods for Smooth Structured Nonconvex-Nonconcave Minimax Problemscited by 62
  4. 2020Halpern Iteration for Near-Optimal and Parameter-Free Monotone Inclusion and Strong Solutions to Variational Inequalitiescited by 61
  5. 2021Extragradient Method: O(1/K) Last-Iterate Convergence for Monotone Variational Inequalities and Connections With Cocoercivitycited by 39
  6. 2022Last-Iterate Convergence of Optimistic Gradient Method for Monotone Variational Inequalitiescited by 33
  7. 2022Exact Optimal Accelerated Complexity for Fixed-Point Iterationscited by 25
  8. 2021Halpern-Type Accelerated and Splitting Algorithms For Monotone Inclusionscited by 21
  9. 2021Optimal error bounds for nonexpansive fixed-point iterations in normed spacescited by 12
  10. 2022Fast Optimistic Gradient Descent Ascent (OGDA) method in continuous and discrete timecited by 10
  11. 2022On modified Halpern and Tikhonov-Mann iterationscited by 3
  12. 2026An Improved Last-Iterate Convergence Rate for Anchored Gradient Descent Ascentcited by 3
5 more
  1. 2026Last-Iterate Convergence of Anchored Gradient Descentcited by 3
  2. 2025Accelerated Extragradient-Type Methods -- Part 2: Generalization and Sublinear Convergence Rates under Co-Hypomonotonicitycited by 2
  3. 2024Tikhonov regularization of monotone operator flows not only ensures strong convergence of the trajectories but also speeds up the vanishing of the residualscited by 1
  4. 2024Extra-Gradient Method with Flexible Anchoring: Strong Convergence and Fast Residual Decaycited by 1
  5. 2025Stochastic Moving Anchor Algorithms and a Popov's Scheme with Moving Anchorcited by 1

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