19 citations · 26 across the 2 of their papers we have counts for
3 papers
Learning To Cut By Looking Ahead: Cutting Plane Selection via Imitation Learning
Max B. Paulus, Giulia Zarpellon, Andreas Krause +2
Cutting planes are essential for solving mixed-integer linear problems (MILPs), because they facilitate bound improvements on the optimal solution value. For selecting cuts, modern…
The Machine Learning for Combinatorial Optimization Competition (ML4CO): Results and Insights
Maxime Gasse, Quentin Cappart, Jonas Charfreitag +38
Combinatorial optimization is a well-established area in operations research and computer science. Until recently, its methods have focused on solving problem instances in isolatio…
Parameterizing Branch-and-Bound Search Trees to Learn Branching Policies
Giulia Zarpellon, Jason Jo, Andrea Lodi +1
Branch and Bound (B&B) is the exact tree search method typically used to solve Mixed-Integer Linear Programming problems (MILPs). Learning branching policies for MILP has become an…