TaeHo Yoon

Downloadable CV here.

Academic Positions

2025-Present

Johns Hopkins University
Rufus Isaacs Postdoctoral Fellow, Dept. of Applied Mathematics & Statistics
Co-worker: Nicolas Loizou

2018-2024

Seoul National University
Ph.D. in Mathematical Sciences
Advisor: Ernest Ryu

2014-2018

Pohang University of Science and Technology
B.S. in Mathematics

May-Aug 2021

AI Vertical Services, AWS
Applied Scientist Intern
Mentors: Youngsuk Park, Bernie Wang

Multiplayer Federated Learning: Reaching Equilibrium with Less Communication. T. Yoon, S. Choudhury and N. Loizou, Manuscript, 2025.
Optimal Acceleration for Minimax and Fixed-Point Problems is Not Unique. T. Yoon, J. Kim, J. J. Suh and E. K. Ryu, ICML, 2024.
- Spotlight paper: Top 335/9473=3.5% of papers.
Censored Sampling of Diffusion Models Using 3 Minutes of Human Feedback. T. Yoon, K. Myoung, K. Lee, J. Cho, A. No and E. K. Ryu, NeurIPS, 2023.
Diffusion Probabilistic Models Generalize when They Fail to Memorize. T. Yoon, J. Choi, S. Kwon and E. K. Ryu, ICML Workshop on Structured Probabilistic Inference & Generative Modeling, 2023.
Accelerated Minimax Algorithms Flock Together. T. Yoon and E. K. Ryu, SIAM Journal on Optimization, 2025.
Robust Probabilistic Time Series Forecasting. T. Yoon, Y. Park, E. K. Ryu and Y. Wang, AISTATS, 2022.
Accelerated Methods for Smooth Convex-Concave Minimax Problems with $\mathcal{O}(1/k^2)$ Rate on Squared Gradient Norm. T. Yoon and E. K. Ryu, ICML, 2021.
- Long presentation: Top 166/5513=3% of papers.
WGAN with an Infinitely Wide Generator Has No Spurious Stationary Points. A. No, T. Yoon, S. Kwon and E. K. Ryu, ICML, 2021.
Joint Transfer of Model Knowledge and Fairness Over Domains Using Wasserstein Distance. T. Yoon, J. Lee and W. Lee, IEEE Access, 2020.