2023
Error Bounds for Learning with Vector-Valued Random Features
NeurIPS 2023spotlight
This paper provides a comprehensive error analysis of learning with vector-valued random features (RF). The theory is developed for RF ridge regression in a fully general infinite-dimensional input-output setting, but nonetheless applies to and improves existing finite-dimensional analyses. In contr…