2020
The Statistical Cost of Robust Kernel Hyperparameter Turning
NeurIPS 2020poster
This paper studies the statistical complexity of kernel hyperparameter tuning in the setting of active regression under adversarial noise. We consider the problem of finding the best interpolant from a class of kernels with unknown hyperparameters, assuming only that the noise is square-integrable.…