13 citations · 20 across the 12 of their papers we have counts for
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cs.LG2023
Matrix Completion in Almost-Verification Time
Jonathan A. Kelner, Jerry Li, Allen Liu +2
We give a new framework for solving the fundamental problem of low-rank matrix completion, i.e., approximating a rank- matrix (where $m…
cs.LG2021
On the Power of Preconditioning in Sparse Linear Regression
Jonathan Kelner, Frederic Koehler, Raghu Meka +1
Sparse linear regression is a fundamental problem in high-dimensional statistics, but strikingly little is known about how to efficiently solve it without restrictive conditions on…
cs.LG2019
Learning Some Popular Gaussian Graphical Models without Condition Number Bounds
Jonathan Kelner, Frederic Koehler, Raghu Meka +1
Gaussian Graphical Models (GGMs) have wide-ranging applications in machine learning and the natural and social sciences. In most of the settings in which they are applied, the numb…