TaeHo Yoon
Downloadable CV here.
Education
2018-Present
2014-2018
Pohang University of Science and Technology
B.S. in Mathematics
B.S. in Mathematics
Work Experiences
May-Aug 2021
Publications
- Optimal Acceleration for Minimax and Fixed-Point Problems is Not Unique. T. Yoon, J. Kim, J. J. Suh and E. K. Ryu, ICML, 2024.
- 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, Manuscript.
- Robust Probabilistic Time Series Forecasting. T. Yoon, Y. Park, E. K. Ryu and Y. Wang, AISTATS, 2022.
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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.
Fellowships and Awards
- Youlchon AI Star Fellowship, 2022.
- Global Ph.D. Fellowship (GPF), 2019-Present.
- Program for Highly Dedicated Students (PHDS) at POSTECH, 2014-2018.