• Corpus ID: 203737226

# The Complexity of Finding Stationary Points with Stochastic Gradient Descent

@inproceedings{Drori2020TheCO,
title={The Complexity of Finding Stationary Points with Stochastic Gradient Descent},
booktitle={ICML},
year={2020}
}
• Published in ICML 4 October 2019
• Computer Science
We study the iteration complexity of stochastic gradient descent (SGD) for minimizing the gradient norm of smooth, possibly nonconvex functions. We provide several results, implying that the classical $\mathcal{O}(\epsilon^{-4})$ upper bound (for making the average gradient norm less than $\epsilon$) cannot be improved upon, unless a combination of additional assumptions is made. Notably, this holds even if we limit ourselves to convex quadratic functions. We also show that for nonconvex…
31 Citations

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