3 papers
cs.LG2025
Neural Logic Networks for Interpretable Classification
Vincent Perreault, Katsumi Inoue, Richard Labib +1
Traditional neural networks have an impressive classification performance, but what they learn cannot be inspected, verified or extracted. Neural Logic Networks on the other hand h…
cs.LG2025
Disentangling Neural Disjunctive Normal Form Models
Kexin Gu Baugh, Vincent Perreault, Matthew Baugh +3
Neural Disjunctive Normal Form (DNF) based models are powerful and interpretable approaches to neuro-symbolic learning and have shown promising results in classification and reinfo…
math.OC2022
A machine learning framework for neighbor generation in metaheuristic search
Defeng Liu, Vincent Perreault, Alain Hertz +1
This paper presents a methodology for integrating machine learning techniques into metaheuristics for solving combinatorial optimization problems. Namely, we propose a general mach…