I am a Founder's Postdoctoral Fellow at Columbia University, Department of Statistics. I received my PhD in Electrical Engineering and Computer Science from MIT, where I was very fortunate to be advised by David Gamarnik. At MIT, I was affiliated with the Laboratory for Information and Decision Systems (LIDS) and the Institute for Data, Systems, and Society (IDSS). You can find my CV here.
I will join the Department of Statistics at the University of Illinois Urbana-Champaign as an assistant professor in Fall 2024.
Planted Random Number Partitioning Problem
Eren C. Kızıldağ
Under review, 2024+
[Paper]
Sharp Phase Transition for Multi Overlap Gap Property in Ising p-Spin Glass and Random k-SAT Models
Eren C. Kızıldağ
Under review, 2024+
[Paper]
Shattering in the Ising Pure p-Spin Model
David Gamarnik, Aukosh Jagannath, Eren C. Kızıldağ
Under review, 2024+
[Paper]
Algorithmic Obstructions in the Random Number Partitioning Problem
David Gamarnik, Eren C. Kızıldağ
Annals of Applied Probability, 2023
[Paper] [Slides] [Talk] [Poster]
Conference version in ISIT 2022
Stationary Points of Shallow Neural Networks with Quadratic Activation Function
David Gamarnik, Eren C. Kızıldağ, Ilias Zadik
Mathematics of Operations Research, 2024
[Paper] [Slides] [Talk]
Symmetric Binary Perceptron with Random Labels: Capacity, Universality, and Overlap Gap Property
Eren C. Kızıldağ, Tanay Wakhare
Preprint, 2023
Self-Regularity of Non-Negative Output Weights for Overparameterized Two-Layer Neural Networks
David Gamarnik, Eren C. Kızıldağ, Ilias Zadik
IEEE Transactions on Signal Processing, 2022
[Paper] [Slides]
Conference version in ISIT 2021
Computing the Partition Function of the Sherrington-Kirkpatrick Model is Hard on Average
David Gamarnik, Eren C. Kızıldağ
Annals of Applied Probability, 2021
[Paper] [Slides]
Conference version in ISIT 2020
Inference in High-Dimensional Linear Regression via Lattice Basis Reduction and Integer Relation Detection
David Gamarnik, Eren C. Kızıldağ, Ilias Zadik
IEEE Transactions on Information Theory, 2021
[Paper]
Neural Networks and Polynomial Regression. Demystifying the Overparametrization Phenomena
Matt Emschwiller, David Gamarnik, Eren C. Kızıldağ, Ilias Zadik
Preprint, 2020
[Paper]
A Random CSP with Connections to Discrepancy Theory and Randomized
Trials
Eren C. Kızıldağ
IEEE International Symposium on Information Theory (ISIT), 2024
[Extended Paper] [Slides]
Geometric Barriers for Stable and Online Algorithms for Discrepancy Minimization
David Gamarnik, Eren C. Kızıldağ, Will Perkins, Changji Xu
Conference on Learning Theory (COLT), 2023
[Paper]
Symmetric Perceptron with Random Labels
Eren C. Kızıldağ, Tanay Wakhare
International Conference on Sampling Theory and Applications (SampTA), 2023
[Paper] [Slides]
Algorithms and Barriers in the Symmetric Binary Perceptron Model
David Gamarnik, Eren C. Kızıldağ, Will Perkins, Changji Xu
IEEE Symposium on Foundations of Computer Science (FOCS), 2022
[Paper] [Slides] [Poster]
The Random Number Partitioning Problem: Overlap Gap Property and Algorithmic Barriers
David Gamarnik, Eren C. Kızıldağ
IEEE International Symposium on Information Theory (ISIT), 2022
[Paper]
Self-Regularity of Output Weights for Overparameterized Two-Layer Neural Networks
David Gamarnik, Eren C. Kızıldağ, Ilias Zadik
IEEE International Symposium on Information Theory (ISIT), 2021
[Paper] [Slides]
Computing the Partition Function of the Sherrington-Kirkpatrick Model is Hard on Average
David Gamarnik, Eren C. Kızıldağ
IEEE International Symposium on Information Theory (ISIT), 2020
[Paper] [Slides]
High-Dimensional Linear Regression and Phase Retrieval via PSLQ Integer
Relation Algorithm
David Gamarnik, Eren C. Kızıldağ
IEEE International Symposium on Information Theory (ISIT), 2019
[Paper] [Slides]
Algorithms and Algorithmic Barriers in
High-Dimensional Statistics and Random
Combinatorial Structures
Ph.D thesis, Massachusetts Institute of Technology, 2022
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