Pretrained neural policies replace repeated GP inference and constrained optimization in safe active learning with a single forward pass, yielding large speedups while preserving query quality.
(7)), named MinUnsafe GP AL: xt = argmax{H[y(x)|y1:t−1, Yinit] − log max(γ, p(z(x) < 0|z1:t−1, Zinit))} (γ = 0 .05, this is the same as Eq
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Amortized Safe Active Learning for Real-Time Data Acquisition: Pretrained Neural Policies From Simulated Nonparametric Functions
Pretrained neural policies replace repeated GP inference and constrained optimization in safe active learning with a single forward pass, yielding large speedups while preserving query quality.