Ilias Zadik
Ilias Zadik
Assistant Professor, Yale University, Department of Statistics and Data Science
Verified email at - Homepage
Cited by
Cited by
Sparse high-dimensional linear regression. Estimating squared error and a phase transition
D Gamarnik, I Zadik
The Annals of Statistics 50 (2), 880-903, 2022
Improved bounds on Gaussian MAC and sparse regression via Gaussian inequalities
I Zadik, Y Polyanskiy, C Thrampoulidis
2019 IEEE International Symposium on Information Theory (ISIT), 430-434, 2019
Revealing network structure, confidentially: Improved rates for node-private graphon estimation
C Borgs, J Chayes, A Smith, I Zadik
2018 IEEE 59th Annual Symposium on Foundations of Computer Science (FOCS …, 2018
The landscape of the planted clique problem: Dense subgraphs and the overlap gap property
D Gamarnik, I Zadik
arXiv preprint arXiv:1904.07174, 2019
Orthogonal machine learning: Power and limitations
I Zadik, L Mackey, V Syrgkanis
International Conference on Machine Learning, 5723-5731, 2018
The all-or-nothing phenomenon in sparse linear regression
G Reeves, J Xu, I Zadik
Conference on Learning Theory, 2652-2663, 2019
Free energy wells and overlap gap property in sparse PCA
GB Arous, AS Wein, I Zadik
Conference on Learning Theory, 479-482, 2020
Lattice-based methods surpass sum-of-squares in clustering
I Zadik, MJ Song, AS Wein, J Bruna
Conference on Learning Theory, 1247-1248, 2022
Mixed-integer convex representability
M Lubin, I Zadik, JP Vielma
Mathematics of Operations Research, 2021
The Franz-Parisi criterion and computational trade-offs in high dimensional statistics
AS Bandeira, A El Alaoui, S Hopkins, T Schramm, AS Wein, I Zadik
Advances in Neural Information Processing Systems 35, 33831-33844, 2022
On the cryptographic hardness of learning single periodic neurons
MJ Song, I Zadik, J Bruna
Advances in neural information processing systems 34, 29602-29615, 2021
Optimal private median estimation under minimal distributional assumptions
C Tzamos, EV Vlatakis-Gkaragkounis, I Zadik
Advances in Neural Information Processing Systems 33, 3301-3311, 2020
All-or-nothing phenomena: From single-letter to high dimensions
G Reeves, J Xu, I Zadik
2019 IEEE 8th International Workshop on Computational Advances in Multi …, 2019
Statistical and computational phase transitions in group testing
A Coja-Oghlan, O Gebhard, M Hahn-Klimroth, AS Wein, I Zadik
Conference on Learning Theory, 4764-4781, 2022
The all-or-nothing phenomenon in sparse tensor PCA
J Niles-Weed, I Zadik
Advances in Neural Information Processing Systems 33, 17674-17684, 2020
Padé approximants, density of rational functions in A∞(Ω) and smoothness of the integration operator
V Nestoridis, I Zadik
Journal of Mathematical Analysis and Applications 423 (2), 1514-1539, 2015
High dimensional linear regression using lattice basis reduction
I Zadik, D Gamarnik
Advances in Neural Information Processing Systems 31, 2018
Almost-linear planted cliques elude the metropolis process
Z Chen, E Mossel, I Zadik
Proceedings of the 2023 Annual ACM-SIAM Symposium on Discrete Algorithms …, 2023
Inference in high-dimensional linear regression via lattice basis reduction and integer relation detection
D Gamarnik, EC Kızıldağ, I Zadik
IEEE Transactions on Information Theory 67 (12), 8109-8139, 2021
Neural networks and polynomial regression. demystifying the overparametrization phenomena
M Emschwiller, D Gamarnik, EC Kızıldağ, I Zadik
arXiv preprint arXiv:2003.10523, 2020
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