no code implementations • 29 Apr 2024 • Fanghui Liu, Leello Dadi, Volkan Cevher
Based on this result, we derive the improved result of metric entropy for $\epsilon$-covering up to $\mathcal{O}(\epsilon^{-\frac{2d}{d+2}})$ ($d$ is the input dimension and the depending constant is at most polynomial order of $d$) via the convex hull technique, which demonstrates the separation with kernel methods with $\Omega(\epsilon^{-d})$ to learn the target function in a Barron space.
