research
∙
05/26/2023
Feature Adaptation for Sparse Linear Regression
Sparse linear regression is a central problem in high-dimensional statis...
share
research
∙
03/01/2023
Sampling with Barriers: Faster Mixing via Lewis Weights
We analyze Riemannian Hamiltonian Monte Carlo (RHMC) for sampling a poly...
research
∙
06/17/2021
On the Power of Preconditioning in Sparse Linear Regression
Sparse linear regression is a fundamental problem in high-dimensional st...
research
∙
12/10/2019
High-precision Estimation of Random Walks in Small Space
In this paper, we provide a deterministic Õ(log N)-space algorithm for e...
research
∙
05/03/2019
Learning Some Popular Gaussian Graphical Models without Condition Number Bounds
Gaussian Graphical Models (GGMs) have wide-ranging applications in machi...
research
∙
11/26/2018