1 citations · 2 across the 3 of their papers we have counts for
3 papers
math.OC2025
Contextual Scenario Generation for Two-Stage Stochastic Programming
David Islip, Roy H. Kwon, Sanghyeon Bae +1
Two-stage stochastic programs (2SPs) are widely used for decision-making under uncertainty, but their practical deployment is often limited by the large number of scenarios needed…
cs.IR2023★ 1 cited
Mean-Variance Efficient Collaborative Filtering for Stock Recommendation
Munki Chung, Junhyeong Lee, Yongjae Lee +1
The rise of FinTech has transformed financial services online, yet stock recommender systems have received limited attention. Personalized stock recommendations can significantly i…
math.OC2022★ 1 cited
Value Function Gradient Learning for Large-Scale Multistage Stochastic Programming Problems
Jinkyu Lee, Sanghyeon Bae, Woo Chang Kim +1
A stagewise decomposition algorithm called value function gradient learning (VFGL) is proposed for large-scale multistage stochastic convex programs. VFGL finds the parameter value…