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2020 – today
- 2020
[j3]Baptiste Bauvin
, Cécile Capponi, Jean-Francis Roy, François Laviolette:
Fast greedy C-bound minimization with guarantees. Mach. Learn. 109(9-10): 1945-1986 (2020)
2010 – 2019
- 2017
- [j2]François Laviolette, Emilie Morvant, Liva Ralaivola, Jean-Francis Roy:
Risk upper bounds for general ensemble methods with an application to multiclass classification. Neurocomputing 219: 15-25 (2017) - 2016
- [c5]Luc Bégin, Pascal Germain, François Laviolette, Jean-Francis Roy:
PAC-Bayesian Bounds based on the Rényi Divergence. AISTATS 2016: 435-444 - [c4]Jean-Francis Roy, Mario Marchand, François Laviolette:
A Column Generation Bound Minimization Approach with PAC-Bayesian Generalization Guarantees. AISTATS 2016: 1241-1249 - 2015
- [j1]Pascal Germain, Alexandre Lacasse, François Laviolette, Mario Marchand, Jean-Francis Roy:
Risk bounds for the majority vote: from a PAC-Bayesian analysis to a learning algorithm. J. Mach. Learn. Res. 16: 787-860 (2015) - [i3]François Laviolette, Emilie Morvant, Liva Ralaivola, Jean-Francis Roy:
On Generalizing the C-Bound to the Multiclass and Multi-label Settings. CoRR abs/1501.03001 (2015) - [i2]Pascal Germain, Alexandre Lacasse, François Laviolette, Mario Marchand, Jean-Francis Roy:
Risk Bounds for the Majority Vote: From a PAC-Bayesian Analysis to a Learning Algorithm. CoRR abs/1503.08329 (2015) - [i1]Louis Fortier-Dubois, François Laviolette, Mario Marchand, Louis-Émile Robitaille, Jean-Francis Roy:
Efficient Learning of Ensembles with QuadBoost. CoRR abs/1506.02535 (2015) - 2014
- [c3]Luc Bégin, Pascal Germain, François Laviolette, Jean-Francis Roy:
PAC-Bayesian Theory for Transductive Learning. AISTATS 2014: 105-113 - 2012
- [c2]Pascal Germain, Sébastien Giguère, Jean-Francis Roy, Brice Zirakiza, François Laviolette, Claude-Guy Quimper:
A Pseudo-Boolean Set Covering Machine. CP 2012: 916-924 - 2011
- [c1]Jean-Francis Roy, François Laviolette, Mario Marchand:
From PAC-Bayes Bounds to Quadratic Programs for Majority Votes. ICML 2011: 649-656
Coauthor Index
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