Ilias Zadik

Orcid: 0000-0002-8286-881X

According to our database1, Ilias Zadik authored at least 34 papers between 2017 and 2024.

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Bibliography

2024
Shapes and recession cones in mixed-integer convex representability.
Math. Program., March, 2024

Counting Stars is Constant-Degree Optimal For Detecting Any Planted Subgraph.
CoRR, 2024

Transfer Learning Beyond Bounded Density Ratios.
CoRR, 2024

2023
It Was "All" for "Nothing": Sharp Phase Transitions for Noiseless Discrete Channels.
IEEE Trans. Inf. Theory, August, 2023

Sharp Thresholds Imply Circuit Lower Bounds: from random 2-SAT to Planted Clique.
CoRR, 2023

Almost-Linear Planted Cliques Elude the Metropolis Process.
Proceedings of the 2023 ACM-SIAM Symposium on Discrete Algorithms, 2023

Sharp thresholds in inference of planted subgraphs.
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.
IEEE Trans. Signal Process., 2022

Mixed-Integer Convex Representability.
Math. Oper. Res., 2022

A second moment proof of the spread lemma.
CoRR, 2022

On the Second Kahn-Kalai Conjecture.
CoRR, 2022

Archimedes Meets Privacy: On Privately Estimating Quantiles in High Dimensions Under Minimal Assumptions.
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.
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.
Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022

Statistical and Computational Phase Transitions in Group Testing.
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.
IEEE Trans. Inf. Theory, 2021

On the Cryptographic Hardness of Learning Single Periodic Neurons.
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.
Proceedings of the IEEE International Symposium on Information Theory, 2021

Group testing and local search: is there a computational-statistical gap?
Proceedings of the Conference on Learning Theory, 2021

2020
Neural Networks and Polynomial Regression. Demystifying the Overparametrization Phenomena.
CoRR, 2020

Optimal Private Median Estimation under Minimal Distributional Assumptions.
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.
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.
Proceedings of the Conference on Learning Theory, 2020

2019
Stationary Points of Shallow Neural Networks with Quadratic Activation Function.
CoRR, 2019

The Landscape of the Planted Clique Problem: Dense subgraphs and the Overlap Gap Property.
CoRR, 2019

Improved bounds on Gaussian MAC and sparse regression via Gaussian inequalities.
Proceedings of the IEEE International Symposium on Information Theory, 2019

A Simple Bound on the BER of the Map Decoder for Massive MIMO Systems.
Proceedings of the IEEE International Conference on Acoustics, 2019

The All-or-Nothing Phenomenon in Sparse Linear Regression.
Proceedings of the Conference on Learning Theory, 2019

All-or-Nothing Phenomena: From Single-Letter to High Dimensions.
Proceedings of the 8th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2019

2018
Private Algorithms Can Always Be Extended.
CoRR, 2018

High Dimensional Linear Regression using Lattice Basis Reduction.
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.
Proceedings of the 35th International Conference on Machine Learning, 2018

Revealing Network Structure, Confidentially: Improved Rates for Node-Private Graphon Estimation.
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.
Proceedings of the 30th Conference on Learning Theory, 2017


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