We introduce a method for online conformal prediction with decaying step sizes. Like previous methods, ours possesses a retrospective guarantee of coverage for arbitrary sequences. However, unlike previous methods, we can simultaneously estimate a population quantile when it exists. Our theory and experiments indicate substantially improved practical properties: in particular, when the distribution is stable, the coverage is close to the desired level for every time point, not just on average over the observed sequence.

翻译：我们提出了一种基于衰减步长的在线共形预测方法。与以往方法相同，本方法对任意序列均具备回顾性覆盖保证。但不同于先前方法的是，我们能在总体分位数存在时对其进行同步估计。理论与实验表明，本方法在实践特性上具有显著优势：特别地，当分布保持稳定时，每个时间点的覆盖水平均接近目标值，而不仅仅是观测序列上的平均值。