4 papers · 1 filter
Multi-task Representation Learning for Mixed Integer Linear Programming
Junyang Cai, Taoan Huang, Bistra Dilkina
Mixed Integer Linear Programs (MILPs) are highly flexible and powerful tools for modeling and solving complex real-world combinatorial optimization problems. Recently, machine lear…
Balans: Multi-Armed Bandits-based Adaptive Large Neighborhood Search for Mixed-Integer Programming Problem
Junyang Cai, Serdar Kadioglu, Bistra Dilkina
Mixed-integer programming (MIP) is a powerful paradigm for modeling and solving various important combinatorial optimization problems. Recently, learning-based approaches have show…
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…
Learning Backdoors for Mixed Integer Linear Programs with Contrastive Learning
Junyang Cai, Taoan Huang, Bistra Dilkina
Many real-world problems can be efficiently modeled as Mixed Integer Linear Programs (MILPs) and solved with the Branch-and-Bound method. Prior work has shown the existence of MILP…