Követés
Gil Kur
Cím
Hivatkozott rá
Hivatkozott rá
Év
Optimality of maximum likelihood for log-concave density estimation and bounded convex regression
G Kur, Y Dagan, A Rakhlin
arXiv preprint arXiv:1903.05315, 2019
42*2019
Projection pursuit in high dimensions
PJ Bickel, G Kur, B Nadler
Proceedings of the National Academy of Sciences 115 (37), 9151-9156, 2018
362018
Double descent in the condition number
T Poggio, G Kur, A Banburski
arXiv preprint arXiv:1912.06190, 2019
312019
Space lower bounds for linear prediction in the streaming model
Y Dagan, G Kur, O Shamir
Conference on Learning Theory, 929-954, 2019
262019
Convex regression in multidimensions: Suboptimality of least squares estimators
G Kur, F Gao, A Guntuboyina, B Sen
arXiv preprint arXiv:2006.02044, 2020
252020
A bounded-noise mechanism for differential privacy
Y Dagan, G Kur
Conference on Learning Theory, 625-661, 2022
232022
Intrinsic and dual volume deviations of convex bodies and polytopes
F Besau, S Hoehner, G Kur
International Mathematics Research Notices 2021 (22), 17456-17513, 2021
152021
On suboptimality of least squares with application to estimation of convex bodies
G Kur, A Rakhlin, A Guntuboyina
Conference on Learning Theory, 2406-2424, 2020
102020
A concentration inequality for random polytopes, Dirichlet–Voronoi tiling numbers and the geometric balls and bins problem
S Hoehner, G Kur
Discrete & Computational Geometry 65, 730-763, 2021
82021
On the minimal error of empirical risk minimization
G Kur, A Rakhlin
Conference on Learning Theory, 2849-2852, 2021
72021
Approximation of the Euclidean ball by polytopes with a restricted number of facets
G Kur
arXiv preprint arXiv:1705.00210, 2017
72017
On the Variance, Admissibility, and Stability of Empirical Risk Minimization
G Kur, E Putterman, A Rakhlin
Advances in Neural Information Processing Systems (spotlight top 3%) 36, 2024
22024
Tyler’s and Maronna’s M-estimators: Non-asymptotic concentration results
E Romanov, G Kur, B Nadler
Journal of Multivariate Analysis 196, 105184, 2023
22023
On The Performance Of The Maximum Likelihood Over Large Models
G Kur
Massachusetts Institute of Technology, 2023
22023
An Efficient Minimax Optimal Estimator For Multivariate Convex Regression
G Kur, E Putterman
Conference on Learning Theory, 1510-1546, 2022
22022
Debiased LASSO under Poisson-Gauss Model
P Abdalla, G Kur
arXiv preprint arXiv:2402.16764, 2024
2024
Minimum Norm Interpolation Meets The Local Theory of Banach Spaces
G Kur, P Abdalla, P Bizeul, F Yang
Forty-first International Conference on Machine Learning, 0
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Cikkek 1–17