Does data interpolation contradict statistical optimality?

This addresses a fundamental question in machine learning theory about the trade-offs between interpolation and statistical efficiency.

The paper tackles the problem of whether data interpolation contradicts statistical optimality, showing that learning methods that interpolate training data can achieve optimal rates for nonparametric regression and prediction with square loss.