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Found 3 papers, 1 papers with code
Learning Backdoors for Mixed Integer Programs with Contrastive Learning
Many real-world problems can be efficiently modeled as Mixed Integer Programs (MIPs) and solved with the Branch-and-Bound method.
Optimization Over Trained Neural Networks: Taking a Relaxing Walk
Besides training, mathematical optimization is also used in deep learning to model and solve formulations over trained neural networks for purposes such as verification, compression, and optimization with learned constraints.
Getting Away with More Network Pruning: From Sparsity to Geometry and Linear Regions
One surprising trait of neural networks is the extent to which their connections can be pruned with little to no effect on accuracy.
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