Computer Science > Machine Learning
arXiv:2605.06741 (cs)
[Submitted on 7 May 2026]
Abstract:Learning-rate steps are usually treated as hyperparameters. This paper isolates a local beliefspace calculation: when an update is modeled as a projected forward step on the probability simplex, admissibility means contractivity in the natural KL/Bregman geometry. Under this model, the upper bound of an admissible step is not a tuning slogan but a formula.
Submission history
From: Youzhen Li [view email]
[v1]
Thu, 7 May 2026 14:28:37 UTC (838 KB)
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