Mario Marchand

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Pascal GermainAssociate Professor, Université LavalVerified email at ift.ulaval.ca
Hugo LarochelleGoogle DeepMind & MilaVerified email at google.com
Jacques CorbeilProfessor of Medicine and Canada Research Chair in Medical GenomicsVerified email at genome.ulaval.ca
Hana AjakanUniversité LavalVerified email at ulaval.ca
Alexandre DrouinLead Research Scientist, ServiceNow Research -- Adjunct Professor of Computer Science, ULaval, MilaVerified email at elementai.com
Victor LempitskyCinemersive LabsVerified email at cinemersivelabs.com
Yaroslav GaninResearch Scientist at Google DeepMindVerified email at google.com
Evgeniya UstinovaSamsung ResearchVerified email at samsung.com
Alexandre LacosteStaff Research Scientist, ServiceNow ResearchVerified email at servicenow.com
John Shawe-TaylorUCLVerified email at cs.ucl.ac.uk
Pal RujanResearch, R-EF GmbHVerified email at r-ef.com
Jean-Francis RoyR&D Director - Machine Learning, CoveoVerified email at ift.ulaval.ca
Mohak ShahManaging Director, Praescivi AdvisorsVerified email at mohakshah.com
Maxime DéraspeUniversité LavalVerified email at ulaval.ca
Marina SokolovaInstitute for Data Analytics@Dal U and University of OttawaVerified email at uottawa.ca
Qi ChenPostdoc, University of Toronto, Vector Institute, Data Science InstituteVerified email at cs.toronto.edu
Pier-Luc PlanteUniversité LavalVerified email at ulaval.ca
Frédéric RaymondUniversité Laval, Associate professorVerified email at fsaa.ulaval.ca
Foutse KhomhNSERC Arthur B. McDonald Fellow, CRC Tier 1, Canada CIFAR AI Chair, FRQ-IVADO Chair, Full ProfessorVerified email at polymtl.ca
Denise TremblayUniversité LavalVerified email at greb.ulaval.ca

Mario Marchand

professeur d'informatique (retraité), Université Laval

Verified email at ift.ulaval.ca

machine learning artificial intelligence


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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	10571	2016
Domain-adversarial neural networks H Ajakan, P Germain, H Larochelle, F Laviolette, M Marchand arXiv preprint arXiv:1412.4446, 2014	444	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	292	2009
A convergence theorem for sequential learning in two-layer perceptrons M Marchand, M Golea, P Ruján Europhysics Letters 11 (6), 487, 1990	216	1990
The set covering machine M Marchand, J Shawe-Taylor The Journal of Machine Learning Research 3, 723-746, 2002	182	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	173	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	159	2019
Predictive computational phenotyping and biomarker discovery using reference-free genome comparisons A Drouin, S Giguère, M Déraspe, M Marchand, M Tyers, VG Loo, ... BMC genomics 17, 1-15, 2016	148	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	129	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	124	2019
A growth algorithm for neural network decision trees M Golea, M Marchand Europhysics Letters 12 (3), 205, 1990	89	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	77	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	74	2011
Learning with Decision Lists of Data-Dependent Features. M Marchand, M Sokolova, MK Warmuth Journal of Machine Learning Research 6 (4), 2005	74	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	72	2015
MHC-NP: predicting peptides naturally processed by the MHC S Giguère, A Drouin, A Lacoste, M Marchand, J Corbeil, F Laviolette Journal of immunological methods 400, 30-36, 2013	63	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	59	1993
Learning by minimizing resources in neural networks M Marchand, P Rujan Complex Systems 3, 229-241, 1989	58	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	55	2013
Agnostic Bayesian learning of ensembles A Lacoste, M Marchand, F Laviolette, H Larochelle International Conference on Machine Learning, 611-619, 2014	53	2014

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