monster-moon Goto Github PK

Hello, I'm Sangjun Moon!

I am statistical analyst who interested in data science. Especially, I have huge interest in convex optimization, neural networks, machine learning, and ranking probability model.

If you want to contact me, please leave me a message!

• Customer-tailored behavioral recommendation research [2020.11 - 2021.03]
• Data Mining Advancement Research [2020.02 - 2020.04]
• Data mining research for AI consulting [2018.01 - 2018.06]

• Analysis of vehicle driving habits through C-ITS analysis [2019.01 - 2019.06]

• Text mining research to discover promising future technologies [2017.04 - 2017.11]

• Sang Jun Moon "Efficient first-order methods for constrained optimization problems" PhD dissertation.
• Gunwoong Park, Sang Jun Moon, Sion Park, and Jong-June Jeon “Learning a High-dimensional Linear Structural Equation Model via l1-Regularized Regression.” Journal of Machine Learning Research 22(102) (2021): 1-41. [link]
• Moon, Sang Jun, et al. “Learning Multiple Quantiles with Neural Networks.” Journal of Computational and Graphical Statistics (2021): 1-27. [link]
• Moon, Sang Jun and Jeon Jong-June “Adaptive Stochastic Gradient Descent method under two mixing heterogenous models.” The Journal of the Korean Data and Information Science Society 28(6) (2017): 1245-1255. [link]

• 2018.03 ~ 2021.08 : University of Seoul, South Korea (Ph.D. in Statistics)
• 2016.03 ~ 2018.02 : University of Seoul, South Korea (M.S. in Statistics)
• 2010.03 ~ 2016.02 : University of Seoul, South Korea (B.S. in Mathmatics)