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Typing assumptions improve identification in causal discovery


Jul 22, 2021
Philippe Brouillard, Perouz Taslakian, Alexandre Lacoste, Sebastien Lachapelle, Alexandre Drouin

* Accepted for presentation as a contributed talk at the Workshop on the Neglected Assumptions in Causal Inference (NACI) at the 38th International Conference on Machine Learning, 2021 

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byteSteady: Fast Classification Using Byte-Level n-Gram Embeddings


Jun 24, 2021
Xiang Zhang, Alexandre Drouin, Raymond Li


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In Search of Robust Measures of Generalization


Oct 22, 2020
Gintare Karolina Dziugaite, Alexandre Drouin, Brady Neal, Nitarshan Rajkumar, Ethan Caballero, Linbo Wang, Ioannis Mitliagkas, Daniel M. Roy

* 27 pages, 11 figures, 34th Conference on Neural Information Processing Systems (NeurIPS 2020), Vancouver, Canada 

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Synbols: Probing Learning Algorithms with Synthetic Datasets


Sep 14, 2020
Alexandre Lacoste, Pau Rodríguez, Frédéric Branchaud-Charron, Parmida Atighehchian, Massimo Caccia, Issam Laradji, Alexandre Drouin, Matt Craddock, Laurent Charlin, David Vázquez


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Differentiable Causal Discovery from Interventional Data


Jul 03, 2020
Philippe Brouillard, SĂ©bastien Lachapelle, Alexandre Lacoste, Simon Lacoste-Julien, Alexandre Drouin

* 34 pages 

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Embedding Propagation: Smoother Manifold for Few-Shot Classification


Mar 09, 2020
Pau RodrĂ­guez, Issam Laradji, Alexandre Drouin, Alexandre Lacoste


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Deep Learning for Electromyographic Hand Gesture Signal Classification Using Transfer Learning


Jun 12, 2018
Ulysse Côté-Allard, Cheikh Latyr Fall, Alexandre Drouin, Alexandre Campeau-Lecours, Clément Gosselin, Kyrre Glette, François Laviolette, Benoit Gosselin

* Source code and datasets available: https://github.com/Giguelingueling/MyoArmbandDataset 

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Maximum Margin Interval Trees


Oct 27, 2017
Alexandre Drouin, Toby Dylan Hocking, François Laviolette

* Accepted for presentation at the 31st Conference on Neural Information Processing Systems (NIPS 2017), Long Beach, CA, USA 

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Large scale modeling of antimicrobial resistance with interpretable classifiers


Dec 03, 2016
Alexandre Drouin, Frédéric Raymond, Gaël Letarte St-Pierre, Mario Marchand, Jacques Corbeil, François Laviolette

* Peer-reviewed and accepted for presentation at the Machine Learning for Health Workshop, NIPS 2016, Barcelona, Spain 

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Greedy Biomarker Discovery in the Genome with Applications to Antimicrobial Resistance


May 22, 2015
Alexandre Drouin, Sébastien Giguère, Maxime Déraspe, François Laviolette, Mario Marchand, Jacques Corbeil

* Peer-reviewed and accepted for an oral presentation in the Greed is Great workshop at the International Conference on Machine Learning, Lille, France, 2015 

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Learning interpretable models of phenotypes from whole genome sequences with the Set Covering Machine


Dec 02, 2014
Alexandre Drouin, Sébastien Giguère, Vladana Sagatovich, Maxime Déraspe, François Laviolette, Mario Marchand, Jacques Corbeil

* Presented at Machine Learning in Computational Biology 2014, Montr\'eal, Qu\'ebec, Canada 

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Learning a peptide-protein binding affinity predictor with kernel ridge regression


Jul 31, 2012
Sébastien Giguère, Mario Marchand, François Laviolette, Alexandre Drouin, Jacques Corbeil

* BMC Bioinformatics 2013, 14:82 
* 22 pages, 4 figures, 5 tables 

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