2 papers
cs.LG2025
A Gap Between the Gaussian RKHS and Neural Networks: An Infinite-Center Asymptotic Analysis
Akash Kumar, Rahul Parhi, Mikhail Belkin
Recent works have characterized the function-space inductive bias of infinite-width bounded-norm single-hidden-layer neural networks as a kind of bounded-variation-type space. This…
cs.LG2024
Mirror Descent on Reproducing Kernel Banach Spaces
Akash Kumar, Mikhail Belkin, Parthe Pandit
Recent advances in machine learning have led to increased interest in reproducing kernel Banach spaces (RKBS) as a more general framework that extends beyond reproducing kernel Hil…