Generalization Bounds for Sparse Random Feature Expansions

2 code implementations • 4 Mar 2021 • Abolfazl Hashemi, Hayden Schaeffer, Robert Shi, Ufuk Topcu, Giang Tran, Rachel Ward

In particular, we provide generalization bounds for functions in a certain class (that is dense in a reproducing kernel Hilbert space) depending on the number of samples and the distribution of features.

BIG-bench Machine Learning Compressive Sensing +1