Deep Learning Theory - Optimization
Part of MSRA project.
Project #1. Large Catapults in Momentum Gradient Descent with Warmup: An Empirical Study
Preliminary version accepted to NeurIPS 2023 Workshop on Mathematics of Modern Machine Learning (M3L) as oral. Currently work in progress with Prin Phunyaphibarn (KAIST Math, intern), Chulhee Yun (KAIST AI), Bohan Wang (USTC), and Huishuai Zhang (Microsoft Research Asia - Theory Centre).
Project #2. A Statistical Analysis of Stochastic Gradient Noises for GNNs
Preliminary work accepted to KCC 2022. Joint work with Minchan Jeong, Namgyu Ho, and Se-Young Yun (KAIST AI).
Junghyun Lee
PhD Student
PhD student at GSAI, KAIST, jointly advised by Prof. Se-Young Yun and Prof. Chulhee Yun. Interested in mathematical and theoretical AI, where I am interested in explaining the recent success of machine/deep learning algorithms and designing mathematically well-grounded algorithms for various scenarios.
