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Subhransu S. Bhattacharjee

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#machine learning Preprint Sep 2026

The cost of useful natural gradient updates

What information is needed to turn a natural-gradient direction into a useful finite update? Under a population Kullback-Leibler (KL) budget, we call a step useful if it is feasible and loses at most a fraction $\varepsilon$ of the best feasible gain along the direction. We construct a four-state exponential family who...

Subhransu S. Bhattacharjee, Dylan Campbell, Rahul Shome · 0 citations

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