论文标题
共形风险控制
Conformal Risk Control
论文作者
论文摘要
我们扩展了共形预测以控制任何单调损耗函数的预期值。该算法将共形预测与其覆盖范围保证一起概括。像共构预测一样，共形风险控制程序紧密至$ \ MATHCAL {O}（1/N）$ factor。我们还介绍了该想法的扩展，以进行分配转移，分数风险控制，多重和对抗性风险控制以及对U统计量的期望。来自计算机视觉和自然语言处理的工作示例证明了我们的算法的用法，以绑定虚假的负率，图形距离和令牌级别的F1得分。
We extend conformal prediction to control the expected value of any monotone loss function. The algorithm generalizes split conformal prediction together with its coverage guarantee. Like conformal prediction, the conformal risk control procedure is tight up to an $\mathcal{O}(1/n)$ factor. We also introduce extensions of the idea to distribution shift, quantile risk control, multiple and adversarial risk control, and expectations of U-statistics. Worked examples from computer vision and natural language processing demonstrate the usage of our algorithm to bound the false negative rate, graph distance, and token-level F1-score.
