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Beyond Optimal Rates in Stochastic Optimization: Trajectory-Adaptive Stopping Rules

This story is from 2026-08-27. It is preserved in the archive; the latest stories are on the live feed.

arXiv:2608.25551v1 Announce Type: cross Abstract: Stochastic gradient descent (SGD) is typically analyzed at a deterministic horizon chosen before the algorithm is run, even though practical stopping decisions are made adaptively by inspecting the evolving trajectory. This mismatch creates a fundam…

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  1. 2026-08-27 04:00 · arXiv stat.ML
    Beyond Optimal Rates in Stochastic Optimization: Trajectory-Adaptive Stopping Rules

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