Gil Kur

According to our database, Gil Kur authored at least 13 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Debiased LASSO under Poisson-Gauss Model.

Pedro Abdalla, Gil Kur

CoRR, 2024

2023

Tyler's and Maronna's M-estimators: Non-asymptotic concentration results.

Elad Romanov, Gil Kur, Boaz Nadler

J. Multivar. Anal., 2023

On the Variance, Admissibility, and Stability of Empirical Risk Minimization.

Gil Kur, Eli Putterman, Alexander Rakhlin

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

Efficient Minimax Optimal Estimators For Multivariate Convex Regression.

Gil Kur, Eli Putterman

CoRR, 2022

An Efficient Minimax Optimal Estimator For Multivariate Convex Regression.

Gil Kur, Eli Putterman

Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022

A bounded-noise mechanism for differential privacy.

Yuval Dagan, Gil Kur

Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022

2021

A Concentration Inequality for Random Polytopes, Dirichlet-Voronoi Tiling Numbers and the Geometric Balls and Bins Problem.

Steven Hoehner, Gil Kur

Discret. Comput. Geom., 2021

On the Minimal Error of Empirical Risk Minimization.

Gil Kur, Alexander Rakhlin

Proceedings of the Conference on Learning Theory, 2021

2020

On Suboptimality of Least Squares with Application to Estimation of Convex Bodies.

Gil Kur, Alexander Rakhlin, Adityanand Guntuboyina

Proceedings of the Conference on Learning Theory, 2020

2019

Double descent in the condition number.

Tomaso A. Poggio, Gil Kur, Andrzej Banburski

CoRR, 2019

The Log-Concave Maximum Likelihood Estimator is Optimal in High Dimensions.

Yuval Dagan, Gil Kur

CoRR, 2019

Space lower bounds for linear prediction.

Yuval Dagan, Gil Kur, Ohad Shamir

CoRR, 2019

Space lower bounds for linear prediction in the streaming model.

Yuval Dagan, Gil Kur, Ohad Shamir

Proceedings of the Conference on Learning Theory, 2019