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Preview of Nonconvex Optimization Bounds
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Nonconvex Optimization Bounds (32_main_paper.pdf)

283 KBEN 10 pages
Stochastic gradient-based optimization algorithms use early stopping based on a validation function. The stopping rule terminates when the gradient norm falls below a threshold. Bounds are derived for expected iterations and gradient evaluations.

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gradient optimization bounds based stopping nonconvex stochastic algorithms early validation function terminates falls threshold derived expected iterations evaluations

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