Almost Sure Convergence Analysis of Stochastic Gradient Methods with Clipping and Additive Noise
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arXiv:2609.12119v1 Announce Type: new Abstract: Stochastic gradient descent (SGD) with gradient clipping and additive noise has become a standard technique for training machine learning models, particularly in applications requiring robustness or privacy guarantees. However, clipping introduces a b…
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- 2026-09-14 04:00 · arXiv cs.LG
Almost Sure Convergence Analysis of Stochastic Gradient Methods with Clipping and Additive Noise
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