1 citations · 2 across the 4 of their papers we have counts for
4 papers
Prediction Loss Guided Decision-Focused Learning
Haeun Jeon, Hyunglip Bae, Chanyeong Kim +2
Decision-making under uncertainty is often considered in two stages: predicting the unknown parameters, and then optimizing decisions based on predictions. While traditional predic…
A Cholesky decomposition-based asset selection heuristic for sparse tangent portfolio optimization
Hyunglip Bae, Haeun Jeon, Minsu Park +2
In practice, including large number of assets in mean-variance portfolios can lead to higher transaction costs and management fees. To address this, one common approach is to selec…
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…
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…