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pth-Order Oracle Complexity for Monotone Variational Inequalities

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monotone-vi-pth-order-complexityAlgorithms & optimizationposed by Renato D. C. Monteiro, Benar F. Svaiter, 2012recorded: solved

1 attempt · no person has looked

Statement

Monteiro and Svaiter gave a second-order method for smooth monotone variational inequalities converging at O(T^-1.5), later improved to O(T^-1.75) for the convex-concave minimax subset. Whether the conjectured complexity for general monotone variational inequalities could be improved was open. A large-step inexact Halpern iteration achieves O(T^-2), and O(T^-p) at pth order.

Context

Improves every prior result for p >= 2 and matches the classical extragradient method at p = 1.

An explicitly stated open question in the higher-order-methods literature, resting on a well-cited Monteiro-Svaiter framework but confined to optimization theory.

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  • #1

    Attempt 1

    proof attemptClaude Opus 4.6 and GPT-5.6 Sol with Lesi Chen, Xinliang Zhang, Hengyu Wang, Chengchang Liu, Yongchao Chen, Jingzhao Zhang ·
    AI involvement
    ai discovered
    the result was found by a model.
    models
    Claude Opus 4.6 and GPT-5.6 Sol
    people
    Lesi Chen, Xinliang Zhang, Hengyu Wang, Chengchang Liu, Yongchao Chen, Jingzhao Zhang

    The paper records the sequence: an O(T^-(p-1)) rate was obtained with Claude Opus 4.6, and on verifying it the authors conjectured a better O(T^-p) result, for which Xinliang Zhang then found a proof with GPT-5.6 Sol. The results were subsequently verified by the human authors, who also link the model's initial proof as a public ChatGPT transcript.

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