The Good, the Bad, and the Sampled: a No-Regret Approach to Safe Online Classification
arXiv:2510.01020v1 Announce Type: cross Abstract: We study the problem of sequentially testing individuals for a binary disease outcome whose true risk is governed by an unknown logistic model. At each round, a patient arrives with feature vector $x_t$, and the…
