A no-regret procedure for safe online logistic classification that meets a target error rate with high probability using only O(sqrt(T)) excess tests over an oracle.
Machine learning portfolio allocation.The Journal of Finance and Data Science, 8:35–54
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The Good, the Bad, and the Sampled: a No-Regret Approach to Safe Online Classification
A no-regret procedure for safe online logistic classification that meets a target error rate with high probability using only O(sqrt(T)) excess tests over an oracle.