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.OC2026
Optimization over Trained (and Sparse) Neural Networks: A Surrogate within a Surrogate
Hung Pham, Aiden Ren, Ibrahim Tahir +2
In constraint learning, we use a neural network as a surrogate for part of the constraints or of the objective function of an optimization model. However, the tractability of the r…