Tianzong Zhang — accepted AI-conference papers

2022

Understanding the Variance Collapse of SVGD in High Dimensions

Jimmy Ba, Murat A Erdogdu, Marzyeh Ghassemi, Shengyang Sun, Taiji Suzuki, Denny Wu +1

ICLR 2022poster

Stein variational gradient descent (SVGD) is a deterministic inference algorithm that evolves a set of particles to fit a target distribution. Despite its computational efficiency, SVGD often underestimates the variance of the target distribution in high dimensions. In this work we attempt to explai…

Cited by 31 Source ↗PDF ↗Scholar ↗

2020

Generalization of Two-layer Neural Networks: An Asymptotic Viewpoint

Jimmy Ba, Murat Erdogdu, Taiji Suzuki, Denny Wu, Tianzong Zhang

ICLR 2020spotlight

This paper investigates the generalization properties of two-layer neural networks in high-dimensions, i.e. when the number of samples $n$, features $d$, and neurons $h$ tend to infinity at the same rate. Specifically, we derive the exact population risk of the unregularized least squares regression…

Cited by 97 Source ↗Scholar ↗