General
On the Rate of Gaussian Approximation for Online Linear Regression Problems
arXiv stat.ML0 views
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 convergence rate on the problem dimension $d$ and quantities related to the design matrix. When the number of iterations $n$ is known in advance, our results yield a normal approximation rate of order $\sqrt{\log{n}/n}$, provided that the sample size $n$ is large enough.
Source:https://arxiv.org/abs/2509.14039PreviousSpectral and Subspace Dynamics of LoRA in Supervised Fine-Tuning and Reinforcement LearningNextVariational Estimators for Node Popularity Models
Related posts
Living Maps: Bay Area tech since 1960s
0Hacker News New
Don't just scale content. Scale creativity
0Hacker News New
Forever,A short browser games you can dare friends to play
0Hacker News New
What to Check Before Installing an Android APK
0Hacker News New
Ask HN: Why do farts smell different when you let them out underwater?
0Hacker News Ask
Jolyboy
0Hacker News Ask