François Laviolette
François Laviolette
Université Laval, Associate member at MILA
Verified email at
TitleCited byYear
Domain-adversarial training of neural networks
Y Ganin, E Ustinova, H Ajakan, P Germain, H Larochelle, F Laviolette, ...
The Journal of Machine Learning Research 17 (1), 2096-2030, 2016
Assemblathon 2: evaluating de novo methods of genome assembly in three vertebrate species
KR Bradnam, JN Fass, A Alexandrov, P Baranay, M Bechner, I Birol, ...
GigaScience 2 (1), 2047-217X-2-10, 2013
Ray: simultaneous assembly of reads from a mix of high-throughput sequencing technologies
S Boisvert, F Laviolette, J Corbeil
Journal of computational biology 17 (11), 1519-1533, 2010
Ray Meta: scalable de novo metagenome assembly and profiling
S Boisvert, F Raymond, É Godzaridis, F Laviolette, J Corbeil
Genome biology 13 (12), R122, 2012
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
Domain-adversarial neural networks
H Ajakan, P Germain, H Larochelle, F Laviolette, M Marchand
arXiv preprint arXiv:1412.4446, 2014
Bisimulation and cocongruence for probabilistic systems
V Danos, J Desharnais, F Laviolette, P Panangaden
Information and Computation 204 (4), 503-523, 2006
Approximate analysis of probabilistic processes: Logic, simulation and games
J Desharnais, F Laviolette, M Tracol
2008 Fifth International Conference on Quantitative Evaluation of Systems …, 2008
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, 769-776, 2007
PAC-Bayesian inequalities for martingales
Y Seldin, F Laviolette, N Cesa-Bianchi, J Shawe-Taylor, P Auer
IEEE Transactions on Information Theory 58 (12), 7086-7093, 2012
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
A PAC-Bayesian approach for domain adaptation with specialization to linear classifiers
P Germain, A Habrard, F Laviolette, E Morvant
International conference on machine learning, 738-746, 2013
Tighter PAC-Bayes bounds through distribution-dependent priors.
G Lever, F Laviolette, J Shawe-Taylor
Theor. Comput. Sci. 473 (Feb), 4-28, 2013
Deep learning for electromyographic hand gesture signal classification using transfer learning
U Côté-Allard, CL Fall, A Drouin, A Campeau-Lecours, C Gosselin, ...
IEEE Transactions on Neural Systems and Rehabilitation Engineering 27 (4 …, 2019
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
On cop-win graphs
G Hahn, F Laviolette, N Sauer, RE Woodrow
Discrete Mathematics 258 (1-3), 27-41, 2002
HIV-1 coreceptor usage prediction without multiple alignments: an application of string kernels
S Boisvert, M Marchand, F Laviolette, J Corbeil
Retrovirology 5 (1), 110, 2008
Transfer learning for sEMG hand gestures recognition using convolutional neural networks
U Cote-Allard, CL Fall, A Campeau-Lecours, C Gosselin, F Laviolette, ...
2017 IEEE International Conference on Systems, Man, and Cybernetics (SMC …, 2017
PAC-Bayesian analysis of contextual bandits
Y Seldin, P Auer, JS Shawe-Taylor, R Ortner, F Laviolette
Advances in neural information processing systems, 1683-1691, 2011
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), 82, 2013
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