ProbXiv
sign in
unchecked

The Axiotis-Sviridenko Condition-Number Conjecture

Nothing has been published against this problem here, and nobody has checked anything. That is the ordinary condition of an open problem, not a defect in the record.

axiotis-sviridenko-condition-number-barrierAlgorithms & optimizationposed by Kyriakos Axiotis, Maxim Sviridenko, 2021recorded: partial

1 attempt · no person has looked

Statement

Axiotis and Sviridenko conjectured that the linear dependence on the restricted condition number in sparse convex optimization cannot be improved by a polynomial-time algorithm. Their conjectured lower bound is established for least-squares objectives, conditional on the randomized exact-volume Small-Set Expansion Hypothesis in the weighted regular-graph formulation of Raghavendra, Steurer and Tulsiani.

Context

Conditional on the randomized exact-volume Small-Set Expansion Hypothesis, and stated for least-squares objectives rather than sparse convex optimization in general.

A 2021 conjecture on the price of sparsity in least squares, sitting in the hardness-of-approximation literature that grew from the Small-Set Expansion Hypothesis.

People

no project yet · nobody looking

Projects

none yet

Nobody is running a project on this. A project is a stated goal, a thread, and one thing somebody else could do. It takes a title, one sentence on what would count as progress, and that one task.

begin a project on this problem →

Interest

nobody looking

Nobody has said they are looking at this. A mark here is a statement about you, not a claim on the problem: you set it, you clear it, and it blocks nobody.

Attempts

1 attempt

No person has examined this. 1 attempt is published here and nothing has been checked against it at all. Saying whether the mathematics holds is the most useful thing anybody can do on this page.

review this attempt

  • #1

    Attempt 1

    proof attemptGemini-based agentic system (internal) with Honghao Lin, Vahab Mirrokni, David P. Woodruff ·
    AI involvement
    ai discovered
    the result was found by a model.
    models
    Gemini-based agentic system (internal)
    people
    Honghao Lin, Vahab Mirrokni, David P. Woodruff

    The acknowledgements state that the proof was first obtained using a fully automated Gemini-based agentic system developed internally at Google, with the authors verifying it and editing for presentation.

    Conditional on the randomized exact-volume Small-Set Expansion Hypothesis, and stated for least-squares objectives rather than sparse convex optimization in general.

    Reviews

    0 human reviews · 0 machine checks

    No person has reviewed this attempt. It has not been checked at all.

    Endorsements

    0 endorsements

    No one has endorsed this attempt. An endorsement is a person stating that they checked this version and believe it is correct. None has been recorded — which is information, not an omission.

    Discussion of this attempt

    no comments

Discussion

no comments

Nothing has been said about this problem yet. Discussion is for questions about the statement, pointers to prior work and objections to an attempt. It is not review: a review is a verdict recorded against one version of one attempt, and it is counted separately.

Reading every thread is open to everyone. Posting needs an account with posting rights — sign in to check yours.