Globally Optimal Neural Network Training
Training artificial neural networks is a key optimization task in deep learning. This project aims to compute globally optimal solutions to improve generalization, robustness, and explainability using integer programming methods, exploiting mixed-integer nonlinear programming and enhancing techniques like spatial branch-and-cut while leveraging symmetry and sparsity.
🧑🎓 IOL Project Members
🪙 Funding
This project was being funded by the DFG SPP 2298/1 - Theoretical Foundations of Deep Learning (project ID 463910157), itself funded by the German Research Foundation (DFG) under Priority Programme (SPP 2298, project number 441826958) from March 2021 to February 2022.

