Mario Marchand
Mario Marchand
professeur d'informatique, Université Laval
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Cited by
Cited by
Domain-adversarial training of neural networks
Y Ganin, E Ustinova, H Ajakan, P Germain, H Larochelle, F Laviolette, ...
Journal of machine learning research 17 (59), 1-35, 2016
Domain-adversarial neural networks
H Ajakan, P Germain, H Larochelle, F Laviolette, M Marchand
arXiv preprint arXiv:1412.4446, 2014
PAC-Bayesian learning of linear classifiers
P Germain, A Lacasse, F Laviolette, M Marchand
Proceedings of the 26th Annual International Conference on Machine Learning …, 2009
A convergence theorem for sequential learning in two-layer perceptrons
M Marchand, M Golea, P Ruján
Europhysics Letters 11 (6), 487, 1990
The set covering machine
M Marchand, J Shawe-Taylor
The Journal of Machine Learning Research 3, 723-746, 2002
Risk bounds for the majority vote: From a PAC-Bayesian analysis to a learning algorithm
P Germain, A Lacasse, F Laviolette, M Marchand, JF Roy
arXiv preprint arXiv:1503.08329, 2015
Predicting ion mobility collision cross-sections using a deep neural network: DeepCCS
PL Plante, É Francovic-Fontaine, JC May, JA McLean, ES Baker, ...
Analytical chemistry 91 (8), 5191-5199, 2019
Predictive computational phenotyping and biomarker discovery using reference-free genome comparisons
A Drouin, S Gigučre, M Déraspe, M Marchand, M Tyers, VG Loo, ...
BMC genomics 17, 1-15, 2016
PAC-Bayes bounds for the risk of the majority vote and the variance of the Gibbs classifier
A Lacasse, F Laviolette, M Marchand, P Germain, N Usunier
Advances in Neural information processing systems 19, 2006
Interpretable genotype-to-phenotype classifiers with performance guarantees
A Drouin, G Letarte, F Raymond, M Marchand, J Corbeil, F Laviolette
Scientific reports 9 (1), 4071, 2019
A growth algorithm for neural network decision trees
M Golea, M Marchand
Europhysics Letters 12 (3), 205, 1990
From PAC-Bayes bounds to quadratic programs for majority votes
F Laviolette, M Marchand, JF Roy
Proceedings of International Conference on Machine Learning, 5-59, 2011
Feature selection with conjunctions of decision stumps and learning from microarray data
M Shah, M Marchand, J Corbeil
IEEE Transactions on Pattern Analysis and Machine Intelligence 34 (1), 174-186, 2011
Learning with Decision Lists of Data-Dependent Features.
M Marchand, M Sokolova, MK Warmuth
Journal of Machine Learning Research 6 (4), 2005
Machine learning assisted design of highly active peptides for drug discovery
S Giguere, F Laviolette, M Marchand, D Tremblay, S Moineau, X Liang, ...
PLoS computational biology 11 (4), e1004074, 2015
MHC-NP: predicting peptides naturally processed by the MHC
S Gigučre, A Drouin, A Lacoste, M Marchand, J Corbeil, F Laviolette
Journal of immunological methods 400, 30-36, 2013
On learning simple neural concepts: from halfspace intersections to neural decision lists
M Marchand, M Golea
Network: Computation in Neural Systems 4 (1), 67-85, 1993
Learning by minimizing resources in neural networks
M Marchand, P Rujan
Complex Systems 3, 229-241, 1989
Learning a peptide-protein binding affinity predictor with kernel ridge regression
S Giguere, M Marchand, F Laviolette, A Drouin, J Corbeil
BMC bioinformatics 14, 1-16, 2013
Agnostic Bayesian learning of ensembles
A Lacoste, M Marchand, F Laviolette, H Larochelle
International Conference on Machine Learning, 611-619, 2014
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