Halyun Jeong
University at Albany, SUNY
Email: hjeong2@albany.edu
I am an Assistant Professor in the Department of Mathematics & Statistics at SUNY Albany.
Previously, I was an Assistant Adjunct Professor at UCLA, where my research mentor was
Professor Deanna Needell. Before that, I was a PIMS postdoctoral fellow at the University of British Columbia, working with
Ozgur Yilmaz,
Yaniv Plan, and
Michael Friedlander. I received my Ph.D. in Mathematics from the
Courant Institute of Mathematical Sciences at New York University in 2017 under the supervision of
Sinan Gunturk.
Research
My research interests span the mathematical aspects of machine learning and signal processing, specifically focusing on the structure of high-dimensional datasets and the convergence guarantees of both convex and non-convex methods that leverage such structures.
Publications
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Stochastic gradient descent for streaming linear and rectified linear systems with adversarial corruptions, SIAM Journal on Mathematics of Data Science (SIMODS), to appear
[arXiv link]
(joint work with Deanna Needell and
Elizaveta Rebrova)
-
Robust Fourier Neural Network, Preprint
[arXiv link]
(joint work with Jihun Han)
-
Nearly Optimal Bounds for Cyclic Forgetting, Neural Information Processing Systems (NeurIPS), 2023
(joint work with
Mark Kong,
William Swartworth , Deanna Needell, and
Rachel Ward)
-
Linear Convergence of Reshuffling Kaczmarz Methods With Sparse Constraints, Preprint [arXiv link]
(joint work with Deanna Needell)
-
Federated Gradient Matching Pursuit, IEEE Transactions on Information Theory, 2024 [journal link]
(joint work with Deanna Needell and
Jing Qin)
-
Polar Deconvolution of mixed signals, IEEE Transactions on Signal Processing, 2022 [journal link]
(joint work with Zhenan Fan, Babhru Joshi, and Michael P. Friedlander)
-
NBIHT: An Efficient Algorithm for 1-bit Compressed Sensing with Optimal Error Decay Rate, IEEE Transactions on Information Theory, 2022 [journal link]
(joint work with Michael P. Friedlander, Yaniv Plan, and Ozgur Yilmaz)
-
Sub-Gaussian Matrices on Sets: Optimal Tail Dependence and Applications, Communications on Pure and Applied Mathematics (CPAM), 2021 [journal link]
(joint work with Xiaowei Li, Yaniv Plan, and Ozgur Yilmaz)
- Atomic Decomposition Via Polar Alignment: The Geometry of Structured Optimization, Foundations and Trends in Optimization, Volume 3:280-366, 2020 [journal link] [pdf]
(joint work with Zhenan Fan, Michael P. Friedlander, and Yifan Sun)
- Non-Gaussian Random Matrices on Sets: Optimal Tail Dependence and Applications, Proceedings of International Conference on Sampling Theory and Applications (SampTA), 2019
(joint work with Xiaowei Li, Yaniv Plan, and Ozgur Yilmaz)
- Are we there yet? Manifold identification of gradient-related proximal methods, Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics (AISTATS), 2019
link.
(joint work with Yifan Sun, Julie Nutini, and Mark Schmidt)
- Convergence of the randomized Kaczmarz method for phase retrieval,
Preprint.
(joint work with Sinan Gunturk)
Recent Talks
-
[Jan 2025] Invited talk at Joint Mathematics Meetings AMS Special Session.
-
[Oct 2024] Invited talk at AMS Fall Eastern Sectional Meeting.
-
[May 2024] Invited talk at SIAM Conference on Applied Linear Algebra 24 minisymposium.
-
[April 2024] Invited talk at the Applied Mathematics Seminar at the University of California, Irvine.
Teaching at SUNY Albany
AMAT 554 Introduction to Theory of Statistics I
Teaching at UCLA
Math156 Machine Learning
Math151B Numerical methods
Math170E Probability and Statistics: Probability
Math170S Probability and Statistics: Statistics
Teaching at UBC
Teaching at NYU
Fall 2016: Calculus 1 recitation
Fall 2015: Honors III (Fourier analysis) recitation
Fall 2014: Algebra and Calculus (Precalculus) recitation