部分验证下的共形预测
Conformal Prediction under Partial Verification
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中文总结 AI 辅助
针对共形预测校准验证成本高的问题，提出部分验证方法，通过协调校准示例间的验证，在保持预测集一致的同时，将验证成本降低15%-82%。
中文摘要 AI 辅助
共形预测能提供具有有限样本保证的预测集，但校准所需的标签验证成本较高。本文提出一种部分验证方法，可返回与完全验证完全相同的预测集；文中定义了校准证书（即确定共形阈值所需的已验证信息），并设计了协调校准示例间验证的流程。对于高覆盖率下的有限阈值，按顺序检查候选时，其验证成本小于最小证书成本的2倍；在检索、数学求解及配置评估任务中，与逐一验证校准示例相比，该方法可将验证成本降低15%-82%，同时生成完全相同的预测集。
英文摘要
Conformal prediction provides prediction sets with finite-sample guarantees, but the label verification required for calibration can be expensive. We develop a partial verification method that returns exactly the same prediction sets as complete verification. We characterize calibration certificates, the verified information sufficient to determine the conformal threshold, and design a procedure that coordinates verification across calibration examples. For finite thresholds at high coverage, its verification cost is less than twice the minimum certificate cost when candidates are checked in order. Across retrieval, mathematical solutions, and configuration evaluation, it reduces verification cost by 15-82% compared with verifying calibration examples one at a time, while producing identical prediction sets.
发表机构
- McGill University（麦吉尔大学）
- Polytechnique de Montréal（蒙特利尔理工学院）
机构由 AI 辅助整理，请以论文原文为准。
