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Courtade and Kumar's Coordinate-wise Mutual Information Question

Probability & statistics · posed by Thomas Courtade, Gowtham Kumar, 2014 · partial

1 attempt

Statement

The Courtade-Kumar conjecture (2014) posits that dictatorship functions maximize mutual information between a Boolean function's output and a noisy input. The paper resolves an open question posed by Courtade and Kumar themselves - a sharp bound of 1H(α)1-H(\alpha) on the sum of coordinate-wise mutual informations for arbitrary bias - and extends the proven high-noise range of the main conjecture via optimal entropy bounds.

Context

Fully resolves the posed coordinate-wise question; the main Courtade-Kumar conjecture itself remains open outside the extended high-noise range.

The Courtade-Kumar conjecture is one of the best-known open problems in the analysis of Boolean functions, attacked steadily since 2014 across information theory and TCS.

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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.

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  • #1

    Attempt 1

    proof attemptGemini Deep Think (larger internal version) with Adel Javanmard, David P. Woodruff ·
    AI involvement
    ai co developed
    a person and a model developed the result together.
    models
    Gemini Deep Think (larger internal version)
    people
    Adel Javanmard, David P. Woodruff

    "The results in this paper were obtained with significant interaction with a larger version of Google's Deep Think Gemini-based model. The authors verified the entire paper and take full responsibility." The acknowledgments thank the Deep Think team by name.

    Fully resolves the posed coordinate-wise question; the main Courtade-Kumar conjecture itself remains open outside the extended high-noise range.

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