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New research details Gaussian approximation rates for online linear regression

By PulseAugur Editorial · [1 sources] ·

A new paper published on arXiv explores the rate of Gaussian approximation for online linear regression problems. The research, authored by Marina Sheshukova, derives convergence rates for a constant stepsize setting. The findings indicate a normal approximation rate of order \(\sqrt{\log{n}/n}\) when the number of iterations \(n\) is known in advance and sufficiently large. AI

IMPACT Provides theoretical insights into approximation rates for a specific class of regression problems, potentially informing future algorithm development.

RANK_REASON Academic paper published on arXiv. [lever_c_demoted from research: ic=1 ai=0.7]

Read on arXiv stat.ML →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New research details Gaussian approximation rates for online linear regression

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Academic paper published on arXiv. [lever_c_demoted from research: ic=1 ai=0.7]
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COVERAGE [1]

  1. arXiv stat.ML TIER_1 English(EN) · Marina Sheshukova, Alain Durmus, Marat Khusainov, Sergey Samsonov ·

    On the Rate of Gaussian Approximation for Online Linear Regression Problems

    arXiv:2509.14039v2 Announce Type: replace Abstract: In this paper, we consider the problem of Gaussian approximation for the online linear regression task. We derive the corresponding rates for the setting of a constant stepsize and study the explicit dependence of the convergenc…

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