From PAC-Bayes Bounds to Quadratic Programs for Majority Votes. - Jean-Francis Roy; François Laviolette; Mario Marchand (ICML, 2011)

A Pseudo-Boolean Set Covering Machine. - Pascal Germain; Sébastien Giguère; Jean-Francis Roy; Brice Zirakiza; François Laviolette; Claude-Guy Quimper (CP, 2012)

PAC-Bayesian Theory for Transductive Learning. - Luc Bégin; Pascal Germain; François Laviolette; Jean-Francis Roy (AISTATS, 2014)

Efficient Learning of Ensembles with QuadBoost. - Louis Fortier-Dubois; François Laviolette; Mario Marchand; Louis-Émile Robitaille; Jean-Francis Roy (CoRR, 2015)

On Generalizing the C-Bound to the Multiclass and Multi-label Settings. - François Laviolette; Emilie Morvant; Liva Ralaivola; Jean-Francis Roy (CoRR, 2015)

Risk bounds for the majority vote: from a PAC-Bayesian analysis to a learning algorithm. - Pascal Germain; Alexandre Lacasse; François Laviolette; Mario Marchand; Jean-Francis Roy (J. Mach. Learn. Res., 2015)

PAC-Bayesian Bounds based on the Rényi Divergence. - Luc Bégin; Pascal Germain; François Laviolette; Jean-Francis Roy (AISTATS, 2016)

A Column Generation Bound Minimization Approach with PAC-Bayesian Generalization Guarantees. - Jean-Francis Roy; Mario Marchand; François Laviolette (AISTATS, 2016)

Risk upper bounds for general ensemble methods with an application to multiclass classification. - François Laviolette; Emilie Morvant; Liva Ralaivola; Jean-Francis Roy (Neurocomputing, 2017)

Fast greedy C-bound minimization with guarantees. - Baptiste Bauvin; Cécile Capponi; Jean-Francis Roy; François Laviolette (Mach. Learn., 2020)

SIGIR 2021 E-Commerce Workshop Data Challenge. - Jacopo Tagliabue; Ciro Greco; Jean-Francis Roy; Bingqing Yu; Patrick John Chia; Federico Bianchi 001; Giovanni Cassani (CoRR, 2021)