2 papers
math.OC2026
Pruning for efficient deterministic global optimization over trained ReLU neural networks
Giacomo Lastrucci, Tanuj Karia, Victor Schulte +2
Neural networks are increasingly used as surrogates in optimization problems to replace computationally expensive models. However, embedding ReLU neural networks in mathematical pr…
math.OC2025
Accelerating Deterministic Global Optimization via GPU-parallel Interval Arithmetic
Hongzhen Zhang, Tim Kerkenhoff, Neil Kichler +4
Spatial Branch and Bound (B&B) algorithms are widely used for solving nonconvex problems to global optimality, yet they remain computationally expensive. Though some works have bee…