Robust Validation: Confident Predictions Even When Distributions Shift
稳健验证：分布漂移下的预测不确定性保障
While the traditional viewpoint in machine learning and statistics assumes training and testing samples come from the same population, practice belies this fiction. One strategy—coming from robust statistics and optimization—is thus to build a model robust to distributional perturbations. In this article, we take a different approach to describe procedures for robust predictive inference, where a model provides uncertainty estimates on its predictions rather than point…