Ilias Zadik

According to our database, Ilias Zadik authored at least 39 papers between 2017 and 2024.

Collaborative distances:

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

2024

Shapes and recession cones in mixed-integer convex representability.

Ilias Zadik, Miles Lubin, Juan Pablo Vielma

Math. Program., March, 2024

Low-degree Security of the Planted Random Subgraph Problem.

Andrej Bogdanov, Chris Jones, Alon Rosen, Ilias Zadik

IACR Cryptol. ePrint Arch., 2024

On The MCMC Performance In Bernoulli Group Testing And The Random Max Set-Cover Problem.

Maxwell Lovig, Ilias Zadik

CoRR, 2024

On the Hardness of Learning One Hidden Layer Neural Networks.

Shuchen Li, Ilias Zadik, Manolis Zampetakis

CoRR, 2024

On the Low-Temperature MCMC threshold: the cases of sparse tensor PCA, sparse regression, and a geometric rule.

Zongchen Chen, Conor Sheehan, Ilias Zadik

CoRR, 2024

Counting Stars is Constant-Degree Optimal For Detecting Any Planted Subgraph.

Xifan Yu, Ilias Zadik, Peiyuan Zhang

CoRR, 2024

Transfer Learning Beyond Bounded Density Ratios.

Alkis Kalavasis, Ilias Zadik, Manolis Zampetakis

CoRR, 2024

Counting Stars is Constant-Degree Optimal For Detecting Any Planted Subgraph: Extended Abstract.

Xifan Yu, Ilias Zadik, Peiyuan Zhang

Proceedings of the Thirty Seventh Annual Conference on Learning Theory, June 30, 2024

2023

It Was "All" for "Nothing": Sharp Phase Transitions for Noiseless Discrete Channels.

Jonathan Niles-Weed, Ilias Zadik

IEEE Trans. Inf. Theory, August, 2023

Sharp Thresholds Imply Circuit Lower Bounds: from random 2-SAT to Planted Clique.

David Gamarnik, Elchanan Mossel, Ilias Zadik

CoRR, 2023

Almost-Linear Planted Cliques Elude the Metropolis Process.

Zongchen Chen, Elchanan Mossel, Ilias Zadik

Proceedings of the 2023 ACM-SIAM Symposium on Discrete Algorithms, 2023

Sharp thresholds in inference of planted subgraphs.

Elchanan Mossel, Jonathan Niles-Weed, Youngtak Sohn, Nike Sun, Ilias Zadik

Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023

2022

Self-Regularity of Non-Negative Output Weights for Overparameterized Two-Layer Neural Networks.

David Gamarnik, Eren C. Kizildag, Ilias Zadik

IEEE Trans. Signal Process., 2022

Mixed-Integer Convex Representability.

Miles Lubin, Juan Pablo Vielma, Ilias Zadik

Math. Oper. Res., 2022

A second moment proof of the spread lemma.

Elchanan Mossel, Jonathan Niles-Weed, Nike Sun, Ilias Zadik

CoRR, 2022

On the Second Kahn-Kalai Conjecture.

Elchanan Mossel, Jonathan Niles-Weed, Nike Sun, Ilias Zadik

CoRR, 2022

Archimedes Meets Privacy: On Privately Estimating Quantiles in High Dimensions Under Minimal Assumptions.

Omri Ben-Eliezer, Dan Mikulincer, Ilias Zadik

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

The Franz-Parisi Criterion and Computational Trade-offs in High Dimensional Statistics.

Afonso S. Bandeira, Ahmed El Alaoui, Samuel B. Hopkins, Tselil Schramm, Alexander S. Wein, Ilias Zadik

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Lattice-Based Methods Surpass Sum-of-Squares in Clustering.

Ilias Zadik, Min Jae Song, Alexander S. Wein, Joan Bruna

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

Statistical and Computational Phase Transitions in Group Testing.

Amin Coja-Oghlan, Oliver Gebhard, Max Hahn-Klimroth, Alexander S. Wein, Ilias Zadik

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

2021

Inference in High-Dimensional Linear Regression via Lattice Basis Reduction and Integer Relation Detection.

David Gamarnik, Eren C. Kizildag, Ilias Zadik

IEEE Trans. Inf. Theory, 2021

On the Cryptographic Hardness of Learning Single Periodic Neurons.

Min Jae Song, Ilias Zadik, Joan Bruna

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Self-Regularity of Output Weights for Overparameterized Two-Layer Neural Networks.

David Gamarnik, Eren C. Kizildag, Ilias Zadik

Proceedings of the IEEE International Symposium on Information Theory, 2021

Group testing and local search: is there a computational-statistical gap?

Fotis Iliopoulos, Ilias Zadik

Proceedings of the Conference on Learning Theory, 2021

2020

Neural Networks and Polynomial Regression. Demystifying the Overparametrization Phenomena.

Matt Emschwiller, David Gamarnik, Eren C. Kizildag, Ilias Zadik

CoRR, 2020

Optimal Private Median Estimation under Minimal Distributional Assumptions.

Christos Tzamos, Emmanouil V. Vlatakis-Gkaragkounis, Ilias Zadik

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

The All-or-Nothing Phenomenon in Sparse Tensor PCA.

Jonathan Niles-Weed, Ilias Zadik

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Free Energy Wells and Overlap Gap Property in Sparse PCA.

Gérard Ben Arous, Alexander S. Wein, Ilias Zadik

Proceedings of the Conference on Learning Theory, 2020

2019

Stationary Points of Shallow Neural Networks with Quadratic Activation Function.

David Gamarnik, Eren C. Kizildag, Ilias Zadik

CoRR, 2019

The Landscape of the Planted Clique Problem: Dense subgraphs and the Overlap Gap Property.

David Gamarnik, Ilias Zadik

CoRR, 2019

Improved bounds on Gaussian MAC and sparse regression via Gaussian inequalities.

Ilias Zadik, Yury Polyanskiy, Christos Thrampoulidis

Proceedings of the IEEE International Symposium on Information Theory, 2019

A Simple Bound on the BER of the Map Decoder for Massive MIMO Systems.

Christos Thrampoulidis, Ilias Zadik, Yury Polyanskiy

Proceedings of the IEEE International Conference on Acoustics, 2019

The All-or-Nothing Phenomenon in Sparse Linear Regression.

Galen Reeves, Jiaming Xu, Ilias Zadik

Proceedings of the Conference on Learning Theory, 2019

All-or-Nothing Phenomena: From Single-Letter to High Dimensions.

Galen Reeves, Jiaming Xu, Ilias Zadik

Proceedings of the 8th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2019

2018

Private Algorithms Can Always Be Extended.

Christian Borgs, Jennifer T. Chayes, Adam D. Smith, Ilias Zadik

CoRR, 2018

High Dimensional Linear Regression using Lattice Basis Reduction.

Ilias Zadik, David Gamarnik

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Orthogonal Machine Learning: Power and Limitations.

Ilias Zadik, Lester W. Mackey, Vasilis Syrgkanis

Proceedings of the 35th International Conference on Machine Learning, 2018

Revealing Network Structure, Confidentially: Improved Rates for Node-Private Graphon Estimation.

Christian Borgs, Jennifer T. Chayes, Adam D. Smith, Ilias Zadik

Proceedings of the 59th IEEE Annual Symposium on Foundations of Computer Science, 2018

2017

High Dimensional Regression with Binary Coefficients. Estimating Squared Error and a Phase Transtition.

David Gamarnik, Ilias Zadik

Proceedings of the 30th Conference on Learning Theory, 2017