2 papers
math.OC2026
Optimization over Trained Neural Networks: Going Large with Gradient-Based Algorithms
Jiatai Tong, Yilin Zhu, Thiago Serra +1
When optimizing a nonlinear objective, one can employ a neural network as a surrogate for the nonlinear function. However, the resulting optimization model can be time-consuming to…
math.OC2025
An Extended Validity Domain for Constraint Learning
Yilin Zhu, Samuel Burer
We consider embedding a predictive machine-learning model within a prescriptive optimization problem. In this setting, called constraint learning, we study the concept of a validit…