77 citations · 318 across the 57 of their papers we have counts for
4 papers · 1 filter
Iteratively reweighted kernel machines efficiently learn sparse functions
Libin Zhu, Damek Davis, Dmitriy Drusvyatskiy +1
The impressive practical performance of neural networks is often attributed to their ability to learn low-dimensional data representations and hierarchical structure directly from…
Spectral norm bound for the product of random Fourier-Walsh matrices
Libin Zhu, Damek Davis, Dmitriy Drusvyatskiy +1
We consider matrix products of the form , where are normalized random Fourier-Walsh matrices. We identify an interesting polyn…
Invariant Kernels: Rank Stabilization and Generalization Across Dimensions
Mateo Díaz, Dmitriy Drusvyatskiy, Jack Kendrick +1
Symmetry arises often when learning from high dimensional data. For example, data sets consisting of point clouds, graphs, and unordered sets appear routinely in contemporary appli…
Online Covariance Estimation in Nonsmooth Stochastic Approximation
Liwei Jiang, Abhishek Roy, Krishna Balasubramanian +3
We consider applying stochastic approximation (SA) methods to solve nonsmooth variational inclusion problems. Existing studies have shown that the averaged iterates of SA methods e…