ReCIRC：修正共形风险控制
ReCIRC: Rectified Conformal Risk Control
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中文总结 AI 辅助
针对共形风险控制因共享阈值导致条件风险不均的问题，提出 ReCIRC 方法，通过反转局部风险曲线实现条件风险控制，在多种任务中降低最差组风险并保持边际风险。
中文摘要 AI 辅助
许多黑盒预测模型的应用需要控制任务相关的错误率，例如分割中遗漏的病变像素或多标签分类中遗漏的标签。共形风险控制（CRC；Angelopoulos 等人，arXiv:2208.02814）为此类损失提供了无分布保证，但它校准了一个所有输入共享的单一阈值。由于条件风险随输入变化，这种边际保证往往过度保护简单案例，而保护不足困难案例。我们提出 ReCIRC（修正共形风险控制），该方法反转每个输入的估计局部风险曲线，将校准阈值重新参数化为风险预算 $a$，代表一个共同的目标条件风险，然后对所得族应用不变的 CRC。ReCIRC 保留了 CRC 的有限样本边际保证，无论估计曲线的准确性如何，而准确的曲线可实现近似条件风险控制，并在额外条件下实现渐近精确的条件风险控制；它们还支持风险校准诊断。在跨越分割、多标签和多类分类以及回归的三个合成和五个真实数据设置中，ReCIRC 在每个设置中都达到了最低的平均最差组风险和平均正组超额，同时保持边际风险接近目标，而预测大小的变化取决于应用。
英文摘要
Many applications of black-box predictive models require controlling task-relevant error rates, such as missed lesion pixels in segmentation or missed labels in multilabel classification. Conformal risk control (CRC; Angelopoulos et al., arXiv:2208.02814) gives distribution-free guarantees for such losses, but it calibrates a single threshold shared by all inputs. Because conditional risk varies with the input, this marginal guarantee often overprotects easy cases and underprotects hard ones. We propose ReCIRC (Rectified Conformal Risk Control), which inverts each input's estimated local risk curve to reparameterize the calibrated threshold as a risk budget $a$ representing a common target conditional risk, and then applies CRC unchanged to the resulting family. ReCIRC retains CRC's finite-sample marginal guarantee regardless of the accuracy of the estimated curves, while accurate curves yield approximate conditional risk control and, under additional conditions, asymptotically exact conditional risk control; they also support a risk-calibration diagnostic. Across three synthetic and five real-data settings spanning segmentation, multilabel and multiclass classification, and regression, ReCIRC attained the lowest average worst-group risk and mean positive group excess in every setting, while maintaining marginal risk close to the target, whereas changes in prediction size were application-dependent.
发表机构
- Federal University of São Carlos（圣卡洛斯联邦大学）
机构由 AI 辅助整理，请以论文原文为准。
