Minhak Song
About Me
Hi! My name is Minhak Song (송민학), and I am an undergraduate student at KAIST, double majoring in Industrial & Systems Engineering and Mathematical Sciences. My research interest lies in building the theoretical foundations of modern machine learning through the lens of optimization theory and statistics. Recently, I have been studying the training dynamics of optimization algorithms in deep learning under the guidance of Prof. Chulhee Yun. Currently, I am a visiting student at the University of Washington, hosted by Prof. Simon Du, where I am working on theoretical aspects of reinforcement learning.
Feel free to reach out for discussions and potential collaborations!
Research Interests
- Machine Learning Theory
- Optimization
- Statistics
News
- [Jan. 2025] Our paper on SGD dynamics along Hessian eigenspaces is accepted to ICLR 2025.
- [Jan. 2025] I joined Prof. Simon Du’s group as a visiting student at the Paul G. Allen School of Computer Science & Engineering at the University of Washington.
- [Jun. 2024] Our paper on SGD dynamics along Hessian eigenspaces is accepted to ICML 2024 Workshop on High-dimensional Learning Dynamics: The Emergence of Structure and Reasoning.
- [Jan. 2024] Our paper on the optimization characteristics of linear Transformers is accepted to ICLR 2024.
- [Oct. 2023] Our paper on the optimization characteristics of linear Transformers is accepted to NeurIPS 2023 Workshop on Mathematics of Modern Machine Learning as an oral presentation.
- [Sep. 2023] Our paper on understanding the Edge of Stability phenomenon in deep learning is accepted to NeurIPS 2023.
Publications
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International Conference on Learning Representations (ICLR), 2025.ICML 2024 Workshop on High-dimensional Learning Dynamics: The Emergence of Structure and Reasoning.
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International Conference on Learning Representations (ICLR), 2024.NeurIPS 2023 Workshop on Mathematics of Modern Machine Learning (Oral).
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Neural Information Processing Systems (NeurIPS), 2023.