Publications

(*: Equal contributions, C: Conference, P: Preprint, S: Seminar)

2026

[S8] A Gradient-Based Method for Stable Solution Search in Nonlinear Constraint Satisfaction Problems

[P3] RAMPing Up PINN Training Signals via Parameter-Sensitivity-Guided Collocation Refinement

[C4] Price-Constrained Demand Forecasting with Zero-inflated Observations for Replenishment and Pricing Decisions

Yujung Byun, Dohyun Bu, Kyungmin Ryu, Jong-Seok Lee
2026 IEEE 22nd International Conference on Automation Science and Engineering (CASE 2026)

[P2] Sparsely-Supervised Data Assimilation via Physics-Informed Schrödinger Bridge [pdf]

[P1] A Unified Neural Architecture for Variable-Wise Shape Constraints [pdf]

[C3] Harmonized Cone for Feasible and Non-conflict Directions in Training Physics-Informed Neural Networks [pdf]

[C2] Covariate-Guided Clusterwise Linear Regression for Generalization to Unseen Data [pdf]

[S7] Stochastic Dual Cone Gradient Descent with Adaptive Moments: A Robust Approach to Conflict-Free Multi-Objective Optimization

[C1] Subject-Adaptive Sparse Linear Models for Interpretable Personalized Health Prediction from Multimodal Lifelog Data [pdf]

[S6] Learning Clusterwise Linear Regression Models using Vector Quantization

[S5] Single-Attempt Hyperparameter Optimization Using Graph Neural Networks

Chanho Kim, Dohyun Bu, Bonyoung Koo, Yulim So, Gaeun Kim, Woo-Jae Lee, Jong-Seok Lee
2024 INFORMS Annual Meeting

[S4] Utilizing Large Language Models for Improved Missing Data Handling in Classification Task

[S3] Enhancing Representation Ability of CNN via Color Inversion Channel

Dohyun Bu, Bonyoung Koo, Chanho Kim, Gaeun Kim, Minjun Jeon, Yulim So, Jong-Seok Lee
2024 INFORMS Annual Meeting

[S2] Learning Regression Models under Order-Preserving Shifts

[S1] Mixture of Locally Monotonic Experts

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