Gil Kur

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20172026

most citedOptimality of Maximum Likelihood for Log-Concave Density Estimation and Bounded Convex Regression

18 citations · 73 across the 13 of their papers we have counts for

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cs.LG2026

Grokking through the Lens of Minimum-Norm Interpolation

Gil Kur, Ileana Rugina, Clémentine Carla Juliette Dominé +1

Grokking shows that fitting the training data and learning the underlying signal can occur at very different stages. However, existing theories offer limited quantitative insight i…

cs.LG2019★ 13 cited

Double descent in the condition number

Tomaso Poggio, Gil Kur, Andrzej Banburski

In solving a system of $n$ linear equations in $d$ variables $A x = b$ , the condition number of the $n, d$ matrix $A$ measures how much errors in the data $b$ affect the solution $x$ .…

cs.LG2019★ 1 cited

Space lower bounds for linear prediction in the streaming model

Yuval Dagan, Gil Kur, Ohad Shamir

We show that fundamental learning tasks, such as finding an approximate linear separator or linear regression, require memory at least \emph{quadratic} in the dimension, in a natur…