2 citations · 2 across the 3 of their papers we have counts for
3 papers
Computational Tradeoffs of Optimization-Based Bound Tightening in ReLU Networks
Fabian Badilla, Marcos Goycoolea, Gonzalo Muñoz +1
The use of Mixed-Integer Linear Programming (MILP) models to represent neural networks with Rectified Linear Unit (ReLU) activations has become increasingly widespread in the last…
Optimization Over Trained Neural Networks: Taking a Relaxing Walk
Jiatai Tong, Junyang Cai, Thiago Serra
Besides training, mathematical optimization is also used in deep learning to model and solve formulations over trained neural networks for purposes such as verification, compressio…
Getting Away with More Network Pruning: From Sparsity to Geometry and Linear Regions
Junyang Cai, Khai-Nguyen Nguyen, Nishant Shrestha +5
One surprising trait of neural networks is the extent to which their connections can be pruned with little to no effect on accuracy. But when we cross a critical level of parameter…