Optimal augmentation size for BONuS under a point-mass prior

Let m~opt\tilde m_{\textnormal{opt}} be the choice of augmentation size that maximizes the power of BONuS for a point-mass prior, with mm fixed. Optimal augmentation-size conjecture.

m~opt=Θ(m).\tilde m_{\textnormal{opt}}=\Theta(\sqrt{m}).

The preceding expansion balances a pseudocount bias of order 1/m~1/\tilde m against learner degradation of order m~/m\tilde m/m, suggesting this scaling. Whether the exact BONuS power has this optimizer remains open.

Sources & referencesView supporting material

Primary source

Abhinav Chakraborty, Junu Lee and Eugene Katsevich, “Power of masking methods for adaptive testing in a multivariate normal means problem”, arXiv:2601.07764 (2026).

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