Data-dependent compression of random features for large-scale kernel approximation

Raj Agrawal, Trevor Campbell, Jonathan H. Huggins, Tamara Broderick

Abstract: Kernel methods offer the flexibility to learn complex relationships in modern, large data sets while enjoying strong theoretical guarantees on quality. Unfortunately, these methods typically requir...