Publications
- Baptiste Bauvin, Cécile Capponi, Jean-Francis Roy, and François Laviolette.
Fast greedy c-bound minimization with guarantees.
Machine Learning, pages 1–42, 2020.
[ Bibtex ]
- Luc Bégin, Pascal Germain, François Laviolette, and Jean-Francis Roy.
Pac-bayesian theory for transductive learning.
In Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics, 105–113. 2014.
[ Bibtex ]
- Luc Bégin, Pascal Germain, François Laviolette, and Jean-Francis Roy.
Pac-bayesian bounds based on the rényi divergence.
In Proceedings of the Nineteenth International Conference on Artificial Intelligence and Statistics, 435–444. 2016.
[ Bibtex ]
- Pascal Germain, Sébastien Giguère, Jean-Francis Roy, Brice Zirakiza, François Laviolette, and Claude-Guy Quimper.
A pseudo-boolean set covering machine.
In Proceedings of the 18th International Conference on Principles and Practice of Constraint Programming, CP 2012, Québec, Canada, 916–924. 2012.
[ Bibtex ]
- Pascal Germain, Alexandre Lacasse, François Laviolette, Mario Marchand, and Jean-Francis Roy.
Risk bounds for the majority vote: from a pac-bayesian analysis to a learning algorithm.
Journal of Machine Learning Research, pages 787–860, 2015.
[ Bibtex ]
- François Laviolette, Emilie Morvant, Liva Ralaivola, and Jean-Francis Roy.
Risk upper bounds for general ensemble methods with an application to multiclass classification.
Neurocomputing, 219:15–25, 2017.
[ Bibtex ]
- François Laviolette, Mario Marchand, and Jean-Francis Roy.
From pac-bayes bounds to quadratic programs for majority votes.
In Proceedings of the 28th International Conference on Machine Learning, ICML 2011, Bellevue, Washington, USA, 649–656. 2011.
[ Bibtex ]
- François Laviolette, Mario Marchand, and Jean-Francis Roy.
Cqboost: a column generation methode for minimizing the c-bound.
In NIPS Workshop on Optimization for Machine Learning. 2014.
[ Bibtex ]
- François Laviolette, Emilie Morvant, Liva Ralaivola, and Jean-Francis Roy.
On generalizing the c-bound to the multiclass and multi-label settings.
In NIPS Workshop on Representation and Learning Methods for Complex Outputs. 2014.
[ Bibtex ]
- Jean-Francis Roy, Mario Marchand, and François Laviolette.
A column generation bound minimization approach with pac-bayesian generalization guarantees.
In Proceedings of the Nineteenth International Conference on Artificial Intelligence and Statistics, 1241–1249. 2016.
[ Bibtex ]