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arXiv Machine Learning By Zijian Liu

In-Expectation Convergence of Stochastic Gradient Methods under Heavy-Tailed Noise

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arXiv:2606. 00520v1 Announce Type: cross Abstract: Many stochastic gradient methods are believed not to converge when the noise in stochastic gradients has only a finite $p$-th moment for $p\in\left(1,2\right)$, a setting known as the heavy-tailed noise assumption.

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