The optimal stopping rule for soft classification of a Brownian drift is characterized by two free boundaries, with explicit asymptotic behavior in the signal-to-noise ratio.
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A Bayesian sequential soft classification problem for a Brownian motion's drift
The optimal stopping rule for soft classification of a Brownian drift is characterized by two free boundaries, with explicit asymptotic behavior in the signal-to-noise ratio.