98 citations · 194 across the 4 of their papers we have counts for
Showing cs.LGShow all
3 papers · 1 filter
cs.LG2020
Hybrid Models for Learning to Branch
Prateek Gupta, Maxime Gasse, Elias B. Khalil +3
A recent Graph Neural Network (GNN) approach for learning to branch has been shown to successfully reduce the running time of branch-and-bound algorithms for Mixed Integer Linear P…
cs.LG2019
Exact Combinatorial Optimization with Graph Convolutional Neural Networks
Maxime Gasse, Didier Chételat, Nicola Ferroni +2
Combinatorial optimization problems are typically tackled by the branch-and-bound paradigm. We propose a new graph convolutional neural network model for learning branch-and-bound…
cs.LG2016
F-measure Maximization in Multi-Label Classification with Conditionally Independent Label Subsets
Maxime Gasse, Alex Aussem
We discuss a method to improve the exact F-measure maximization algorithm called GFM, proposed in (Dembczynski et al. 2011) for multi-label classification, assuming the label set c…