Data-driven algorithm design using neural networks with applications to branch-and-cut

no code implementations • 4 Feb 2024 • Hongyu Cheng, Sammy Khalife, Barbara Fiedorowicz, Amitabh Basu

We build upon recent work in this line of research by introducing the idea where, instead of selecting a single algorithm that has the best performance, we allow the possibility of selecting an algorithm based on the instance to be solved.

Neural networks with linear threshold activations: structure and algorithms

no code implementations • 15 Nov 2021 • Sammy Khalife, Hongyu Cheng, Amitabh Basu

We precisely characterize the class of functions that are representable by such neural networks and show that 2 hidden layers are necessary and sufficient to represent any function representable in the class.