Feb. 13, 2024, 5:44 a.m. | Rotem Mulayoff Tomer Michaeli

cs.LG updates on arXiv.org arxiv.org

The dynamical stability of optimization methods at the vicinity of minima of the loss has recently attracted significant attention. For gradient descent (GD), stable convergence is possible only to minima that are sufficiently flat w.r.t. the step size, and those have been linked with favorable properties of the trained model. However, while the stability threshold of GD is well-known, to date, no explicit expression has been derived for the exact threshold of stochastic GD (SGD). In this paper, we derive …

analysis attention convergence cs.lg gradient linear loss mean optimization square stability

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