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2020 – today
- 2024
[j5]Ilias Zadik, Miles Lubin
, Juan Pablo Vielma:
Shapes and recession cones in mixed-integer convex representability. Math. Program. 204(1): 739-752 (2024)- [c24]Xifan Yu, Ilias Zadik, Peiyuan Zhang:
Counting Stars is Constant-Degree Optimal For Detecting Any Planted Subgraph: Extended Abstract. COLT 2024: 5163-5165 - [c23]Andrej Bogdanov, Chris Jones, Alon Rosen, Ilias Zadik:
Low-Degree Security of the Planted Random Subgraph Problem. TCC (2) 2024: 255-275 - [i32]Alkis Kalavasis, Ilias Zadik, Manolis Zampetakis:
Transfer Learning Beyond Bounded Density Ratios. CoRR abs/2403.11963 (2024) - [i31]Xifan Yu, Ilias Zadik, Peiyuan Zhang:
Counting Stars is Constant-Degree Optimal For Detecting Any Planted Subgraph. CoRR abs/2403.17766 (2024) - [i30]Zongchen Chen, Conor Sheehan, Ilias Zadik:
On the Low-Temperature MCMC threshold: the cases of sparse tensor PCA, sparse regression, and a geometric rule. CoRR abs/2408.00746 (2024) - [i29]Andrej Bogdanov, Chris Jones, Alon Rosen, Ilias Zadik:
Low-degree Security of the Planted Random Subgraph Problem. CoRR abs/2409.16227 (2024) - [i28]Shuchen Li, Ilias Zadik, Manolis Zampetakis:
On the Hardness of Learning One Hidden Layer Neural Networks. CoRR abs/2410.03477 (2024) - [i27]Maxwell Lovig, Ilias Zadik:
On The MCMC Performance In Bernoulli Group Testing And The Random Max Set-Cover Problem. CoRR abs/2410.09231 (2024) - [i26]Andrej Bogdanov, Chris Jones, Alon Rosen, Ilias Zadik:
Low-degree Security of the Planted Random Subgraph Problem. IACR Cryptol. ePrint Arch. 2024: 1497 (2024) - 2023
- [j4]Jonathan Niles-Weed, Ilias Zadik:
It Was "All" for "Nothing": Sharp Phase Transitions for Noiseless Discrete Channels. IEEE Trans. Inf. Theory 69(8): 5188-5202 (2023) - [c22]Elchanan Mossel, Jonathan Niles-Weed, Youngtak Sohn, Nike Sun, Ilias Zadik:
Sharp thresholds in inference of planted subgraphs. COLT 2023: 5573-5577 - [c21]Zongchen Chen, Elchanan Mossel, Ilias Zadik:
Almost-Linear Planted Cliques Elude the Metropolis Process. SODA 2023: 4504-4539 - [i25]Elchanan Mossel, Jonathan Niles-Weed, Youngtak Sohn, Nike Sun, Ilias Zadik:
Sharp thresholds in inference of planted subgraphs. CoRR abs/2302.14830 (2023) - [i24]David Gamarnik, Elchanan Mossel, Ilias Zadik:
Sharp Thresholds Imply Circuit Lower Bounds: from random 2-SAT to Planted Clique. CoRR abs/2311.04204 (2023) - 2022
- [j3]Miles Lubin, Juan Pablo Vielma, Ilias Zadik:
Mixed-Integer Convex Representability. Math. Oper. Res. 47(1): 720-749 (2022) - [j2]David Gamarnik, Eren C. Kizildag, Ilias Zadik:
Self-Regularity of Non-Negative Output Weights for Overparameterized Two-Layer Neural Networks. IEEE Trans. Signal Process. 70: 1310-1319 (2022) - [c20]Ilias Zadik, Min Jae Song, Alexander S. Wein, Joan Bruna:
Lattice-Based Methods Surpass Sum-of-Squares in Clustering. COLT 2022: 1247-1248 - [c19]Amin Coja-Oghlan, Oliver Gebhard, Max Hahn-Klimroth, Alexander S. Wein, Ilias Zadik:
Statistical and Computational Phase Transitions in Group Testing. COLT 2022: 4764-4781 - [c18]Afonso S. Bandeira, Ahmed El Alaoui, Samuel B. Hopkins, Tselil Schramm, Alexander S. Wein, Ilias Zadik:
The Franz-Parisi Criterion and Computational Trade-offs in High Dimensional Statistics. NeurIPS 2022 - [c17]Omri Ben-Eliezer, Dan Mikulincer, Ilias Zadik:
Archimedes Meets Privacy: On Privately Estimating Quantiles in High Dimensions Under Minimal Assumptions. NeurIPS 2022 - [i23]Zongchen Chen, Elchanan Mossel, Ilias Zadik:
Almost-Linear Planted Cliques Elude the Metropolis Process. CoRR abs/2204.01911 (2022) - [i22]Afonso S. Bandeira, Ahmed El Alaoui, Samuel B. Hopkins, Tselil Schramm, Alexander S. Wein, Ilias Zadik:
The Franz-Parisi Criterion and Computational Trade-offs in High Dimensional Statistics. CoRR abs/2205.09727 (2022) - [i21]Amin Coja-Oghlan, Oliver Gebhard, Max Hahn-Klimroth, Alexander S. Wein, Ilias Zadik:
Statistical and Computational Phase Transitions in Group Testing. CoRR abs/2206.07640 (2022) - [i20]Omri Ben-Eliezer, Dan Mikulincer, Ilias Zadik:
Archimedes Meets Privacy: On Privately Estimating Quantiles in High Dimensions Under Minimal Assumptions. CoRR abs/2208.07438 (2022) - [i19]Elchanan Mossel, Jonathan Niles-Weed, Nike Sun, Ilias Zadik:
On the Second Kahn-Kalai Conjecture. CoRR abs/2209.03326 (2022) - [i18]Elchanan Mossel, Jonathan Niles-Weed, Nike Sun, Ilias Zadik:
A second moment proof of the spread lemma. CoRR abs/2209.11347 (2022) - 2021
- [j1]David Gamarnik, Eren C. Kizildag, Ilias Zadik:
Inference in High-Dimensional Linear Regression via Lattice Basis Reduction and Integer Relation Detection. IEEE Trans. Inf. Theory 67(12): 8109-8139 (2021) - [c16]Fotis Iliopoulos, Ilias Zadik:
Group testing and local search: is there a computational-statistical gap? COLT 2021: 2499-2551 - [c15]Jonathan Niles-Weed, Ilias Zadik:
It was "all" for "nothing": sharp phase transitions for noiseless discrete channels. COLT 2021: 3546-3547 - [c14]David Gamarnik, Eren C. Kizildag, Ilias Zadik:
Self-Regularity of Output Weights for Overparameterized Two-Layer Neural Networks. ISIT 2021: 819-824 - [c13]Min Jae Song, Ilias Zadik, Joan Bruna:
On the Cryptographic Hardness of Learning Single Periodic Neurons. NeurIPS 2021: 29602-29615 - [i17]Jonathan Niles-Weed, Ilias Zadik:
It was "all" for "nothing": sharp phase transitions for noiseless discrete channels. CoRR abs/2102.12422 (2021) - [i16]David Gamarnik, Eren C. Kizildag, Ilias Zadik:
Self-Regularity of Non-Negative Output Weights for Overparameterized Two-Layer Neural Networks. CoRR abs/2103.01887 (2021) - [i15]Min Jae Song, Ilias Zadik, Joan Bruna:
On the Cryptographic Hardness of Learning Single Periodic Neurons. CoRR abs/2106.10744 (2021) - [i14]Ilias Zadik, Min Jae Song, Alexander S. Wein, Joan Bruna:
Lattice-Based Methods Surpass Sum-of-Squares in Clustering. CoRR abs/2112.03898 (2021) - 2020
- [c12]Gérard Ben Arous, Alexander S. Wein, Ilias Zadik:
Free Energy Wells and Overlap Gap Property in Sparse PCA. COLT 2020: 479-482 - [c11]Jonathan Niles-Weed, Ilias Zadik:
The All-or-Nothing Phenomenon in Sparse Tensor PCA. NeurIPS 2020 - [c10]Christos Tzamos, Emmanouil V. Vlatakis-Gkaragkounis, Ilias Zadik:
Optimal Private Median Estimation under Minimal Distributional Assumptions. NeurIPS 2020 - [i13]Matt Emschwiller, David Gamarnik, Eren C. Kizildag, Ilias Zadik:
Neural Networks and Polynomial Regression. Demystifying the Overparametrization Phenomena. CoRR abs/2003.10523 (2020) - [i12]Gérard Ben Arous, Alexander S. Wein, Ilias Zadik:
Free Energy Wells and Overlap Gap Property in Sparse PCA. CoRR abs/2006.10689 (2020) - [i11]Jonathan Niles-Weed, Ilias Zadik:
The All-or-Nothing Phenomenon in Sparse Tensor PCA. CoRR abs/2007.11138 (2020) - [i10]Fotis Iliopoulos, Ilias Zadik:
Group testing and local search: is there a computational-statistical gap? CoRR abs/2011.05258 (2020) - [i9]Christos Tzamos, Emmanouil V. Vlatakis-Gkaragkounis, Ilias Zadik:
Optimal Private Median Estimation under Minimal Distributional Assumptions. CoRR abs/2011.06202 (2020)
2010 – 2019
- 2019
- [c9]Galen Reeves, Jiaming Xu, Ilias Zadik:
All-or-Nothing Phenomena: From Single-Letter to High Dimensions. CAMSAP 2019: 654-658 - [c8]Galen Reeves, Jiaming Xu, Ilias Zadik:
The All-or-Nothing Phenomenon in Sparse Linear Regression. COLT 2019: 2652-2663 - [c7]Christos Thrampoulidis, Ilias Zadik, Yury Polyanskiy:
A Simple Bound on the BER of the Map Decoder for Massive MIMO Systems. ICASSP 2019: 4544-4548 - [c6]Ilias Zadik, Yury Polyanskiy, Christos Thrampoulidis:
Improved bounds on Gaussian MAC and sparse regression via Gaussian inequalities. ISIT 2019: 430-434 - [i8]Christos Thrampoulidis, Ilias Zadik, Yury Polyanskiy:
A simple bound on the BER of the MAP decoder for massive MIMO systems. CoRR abs/1903.03949 (2019) - [i7]Galen Reeves, Jiaming Xu, Ilias Zadik:
The All-or-Nothing Phenomenon in Sparse Linear Regression. CoRR abs/1903.05046 (2019) - [i6]David Gamarnik, Ilias Zadik:
The Landscape of the Planted Clique Problem: Dense subgraphs and the Overlap Gap Property. CoRR abs/1904.07174 (2019) - [i5]David Gamarnik, Eren C. Kizildag, Ilias Zadik:
Stationary Points of Shallow Neural Networks with Quadratic Activation Function. CoRR abs/1912.01599 (2019) - [i4]Galen Reeves, Jiaming Xu, Ilias Zadik:
All-or-Nothing Phenomena: From Single-Letter to High Dimensions. CoRR abs/1912.13027 (2019) - 2018
- [c5]Christian Borgs, Jennifer T. Chayes, Adam D. Smith, Ilias Zadik:
Revealing Network Structure, Confidentially: Improved Rates for Node-Private Graphon Estimation. FOCS 2018: 533-543 - [c4]Ilias Zadik, Lester W. Mackey, Vasilis Syrgkanis:
Orthogonal Machine Learning: Power and Limitations. ICML 2018: 5723-5731 - [c3]Ilias Zadik, David Gamarnik:
High Dimensional Linear Regression using Lattice Basis Reduction. NeurIPS 2018: 1847-1857 - [i3]Christian Borgs, Jennifer T. Chayes, Adam D. Smith, Ilias Zadik:
Revealing Network Structure, Confidentially: Improved Rates for Node-Private Graphon Estimation. CoRR abs/1810.02183 (2018) - [i2]Christian Borgs, Jennifer T. Chayes, Adam D. Smith, Ilias Zadik:
Private Algorithms Can Always Be Extended. CoRR abs/1810.12518 (2018) - 2017
- [c2]David Gamarnik, Ilias Zadik:
High Dimensional Regression with Binary Coefficients. Estimating Squared Error and a Phase Transtition. COLT 2017: 948-953 - [c1]Miles Lubin, Ilias Zadik, Juan Pablo Vielma:
Mixed-Integer Convex Representability. IPCO 2017: 392-404 - [i1]Lester W. Mackey, Vasilis Syrgkanis, Ilias Zadik:
Orthogonal Machine Learning: Power and Limitations. CoRR abs/1711.00342 (2017)
Coauthor Index
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last updated on 2024-12-12 21:57 CET by the dblp team
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