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Ilias Zadik
Ilias Zadik
Postdoctoral Associate, MIT Mathematics Department
Verified email at mit.edu - Homepage
Title
Cited by
Cited by
Year
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
75*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
402019
The all-or-nothing phenomenon in sparse linear regression
G Reeves, J Xu, I Zadik
Mathematical Statistics and Learning 3 (3), 259-313, 2021
352021
Orthogonal machine learning: Power and limitations
I Zadik, L Mackey, V Syrgkanis
International Conference on Machine Learning, 5723-5731, 2018
29*2018
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
272018
Mixed-integer convex representability
M Lubin, I Zadik, JP Vielma
Mathematics of Operations Research, 2021
24*2021
The landscape of the planted clique problem: Dense subgraphs and the overlap gap property
D Gamarnik, I Zadik
arXiv preprint arXiv:1904.07174, 2019
232019
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
162019
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
162015
Free energy wells and overlap gap property in sparse PCA
GB Arous, AS Wein, I Zadik
Conference on Learning Theory, 479-482, 2020
152020
The all-or-nothing phenomenon in sparse tensor PCA
J Niles-Weed, I Zadik
Advances in Neural Information Processing Systems 33, 17674-17684, 2020
142020
High dimensional linear regression using lattice basis reduction
I Zadik, D Gamarnik
Advances in Neural Information Processing Systems 31, 2018
132018
Neural networks and polynomial regression. demystifying the overparametrization phenomena
M Emschwiller, D Gamarnik, EC Kızıldağ, I Zadik
arXiv preprint arXiv:2003.10523, 2020
102020
A simple bound on the ber of the map decoder for massive mimo systems
C Thrampoulidis, I Zadik, Y Polyanskiy
ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and …, 2019
92019
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
72020
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
62021
Stationary points of shallow neural networks with quadratic activation function
D Gamarnik, EC Kızıldağ, I Zadik
arXiv preprint arXiv:1912.01599, 2019
62019
Computational and statistical challenges in high dimensional statistical models
I Zadik
Massachusetts Institute of Technology, 2019
62019
Lattice-based methods surpass sum-of-squares in clustering
I Zadik, MJ Song, AS Wein, J Bruna
arXiv preprint arXiv:2112.03898, 2021
52021
It was “all” for “nothing”: sharp phase transitions for noiseless discrete channels
J Niles-Weed, I Zadik
Conference on Learning Theory, 3546-3547, 2021
52021
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