About Me
Hi! My name is Minhak Song, and I am an undergraduate student at KAIST, majoring in Mathematical Sciences (minor in Industrial and Systems Engineering). My research interests center on the theoretical foundations of modern machine learning, with the goal of bridging theory and practice.
I have recently been studying the training dynamics of optimization algorithms in deep learning, advised by Prof. Chulhee Yun. I was also a visiting student at the University of Washington, hosted by Prof. Simon Du, where I worked on reinforcement learning from human feedback (RLHF) from an optimization perspective. This summer, I am working with Prof. Sewoong Oh at UW on zeroth-order optimization.
I’m always open to conversations and potential collaborations. Feel free to reach out!
Research Interests
- Deep Learning Theory
- Optimization
News
Publications
(* denotes equal contribution)
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Minhak Song*, Beomhan Baek*, Kwangjun Ahn, Chulhee Yun
ICML 2025 Workshop on High-dimensional Learning Dynamics.
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Ruizhe Shi*, Minhak Song*, Runlong Zhou, Zihan Zhang, Maryam Fazel, Simon Du
Manuscript, 2025.
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Geonhui Yoo, Minhak Song, Chulhee Yun
International Conference on Machine Learning (ICML), 2025.
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Minhak Song, Kwangjun Ahn, Chulhee Yun
International Conference on Learning Representations (ICLR), 2025.
ICML 2024 Workshop on High-dimensional Learning Dynamics.
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Kwangjun Ahn*, Xiang Cheng*, Minhak Song*, Chulhee Yun, Ali Jadbabaie, Suvrit Sra
International Conference on Learning Representations (ICLR), 2024.
NeurIPS 2023 Workshop on Mathematics of Modern Machine Learning (Oral).
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Minhak Song, Chulhee Yun
Neural Information Processing Systems (NeurIPS), 2023.
Services
Conference/Workshop Reviewer