Laurent Charlin

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Membre Académique Principal
Laurent Charlin
Professeur agrégé, HEC Montréal
Laurent Charlin

Laurent Charlin est un professeur agrégé au département des sciences de la décision à HEC Montréal. Ses champs d’intérêt sont l’apprentissage automatique (machine learning) et en particulier les modèles probabilistes générateurs pour la prise de décision. Plusieurs de ses contributions portent sur ces méthodes appliquées aux systèmes de recommandations.

Le Toronto Paper Matching System (TPMS), qu’il a codéveloppé, est un système ayant pour but d’aider les organisateurs de conférences à apparier les soumissions d’articles aux relecteurs de la conférence. Depuis plusieurs années ce système est utilisé mondialement par les plus importantes conférences en apprentissage statistique et en vision artificielle.

Laurent a obtenu un diplôme d’ingénieur de l’École Polytechnique de Montréal, une maîtrise de l’Université de Waterloo et un doctorat de l’Université de Toronto. Il a aussi poursuivi des études postdoctorales aux universités Princeton et Columbia ainsi qu’à l’Université McGill.

Publications

2021-06

Pretraining Representations for Data-Efficient Reinforcement Learning.
Max Schwarzer, Nitarshan Rajkumar, Michael Noukhovitch, Ankesh Anand, Laurent Charlin, R. Devon Hjelm, Philip Bachman and Aaron C. Courville
arXiv preprint arXiv:2106.04799
(2021-06-09)
dblp.uni-trier.dePDF

2021-05

Beyond Trivial Counterfactual Generations with Diverse Valuable Explanations
Pau Rodriguez, Massimo Caccia, Alexandre Lacoste, Lee Zamparo, Issam H. Laradji, Laurent Charlin and David Vazquez
arxiv:cs.LG
(2021-05-04)
dblp.uni-trier.dePDF

2021-04

Comparative Study of Learning Outcomes for Online Learning Platforms
Francois St-Hilaire, Nathan Burns, Robert Belfer, Muhammad Shayan, Ariella Smofsky, Dung Do Vu, Antoine Frau, Joseph Potochny, Farid Faraji, Vincent Pavero, Neroli Ko, Ansona Onyi Ching, Sabina Elkins, Anush Stepanyan, Adela Matajova, Laurent Charlin, Yoshua Bengio, Iulian Vlad Serban and Ekaterina Kochmar
arXiv preprint arXiv:2104.07763
(2021-04-15)
arxiv.orgPDF
IG-RL: Inductive Graph Reinforcement Learning for Massive-Scale Traffic Signal Control
François-Xavier Devailly, Denis Larocque and Laurent Charlin
IEEE Transactions on Intelligent Transportation Systems
(2021-04-15)
ieeexplore.ieee.org[Also on arXiv: Learning (2020-03-06)]
A Comparative Study of Learning Outcomes for Online Learning Platforms
François St-Hilaire, Nathan Burns, Robert Belfer, Muhammad Shayan, Ariella Smofsky, Dung Do Vu, Antoine Frau, Joseph Potochny, Farid Faraji, Vincent Pavero, Neroli Ko, Ansona Onyi Ching, Sabina Elkins, Anush Stepanyan, Adela Matajova, Laurent Charlin, Yoshua Bengio, Iulian Vlad Serban and Ekaterina Kochmar
AIED 2021
(2021-04-05)
researchportal.bath.ac.uk

2021-03

Pretraining Reward-Free Representations for Data-Efficient Reinforcement Learning
Max Schwarzer, Nitarshan Rajkumar, Michael Noukhovitch, Ankesh Anand, Laurent Charlin, R Devon Hjelm, Philip Bachman and Aaron Courville
ICLR 2021
(2021-03-09)
openreview.netPDF

2020-11

Multi-XScience: A Large-scale Dataset for Extreme Multi-document Summarization of Scientific Articles
Yao Lu, Yue Dong and Laurent Charlin

2020-09

Causal Inference for Recommender Systems
Yixin Wang, Dawen Liang, Laurent Charlin and David M. Blei
RECSYS 2020
(2020-09-22)
dl.acm.org
Synbols: Probing Learning Algorithms with Synthetic Datasets
Alexandre Lacoste, Pau Rodríguez López, Frederic Branchaud-Charron, Parmida Atighehchian, Massimo Caccia, Issam Hadj Laradji, Alexandre Drouin, Matthew Craddock, Laurent Charlin and David Vázquez
NEURIPS 2020
(2020-09-14)
papers.nips.ccPDF
Synbols: Probing Learning Algorithms with Synthetic Datasets
Alexandre Lacoste, Pau Rodríguez, Frédéric Branchaud-Charron, Parmida Atighehchian, Massimo Caccia, Issam Laradji, Alexandre Drouin, Matt Craddock, Laurent Charlin and David Vázquez
arXiv preprint arXiv:2009.06415
(2020-09-14)
ui.adsabs.harvard.eduPDF
On the Effectiveness of Two-Step Learning for Latent-Variable Models
Cem Subakan, Maxime Gasse and Laurent Charlin
MLSP 2020
(2020-09-01)
doi.org

2020-07

A Large-Scale, Open-Domain, Mixed-Interface Dialogue-Based ITS for STEM
Iulian Vlad Serban, Varun Gupta, Ekaterina Kochmar, Dung Do Vu, Robert Belfer, Joelle Pineau, Aaron C. Courville, Laurent Charlin and Yoshua Bengio

2020-04

Language GANs Falling Short
Massimo Caccia, Lucas Caccia, William Fedus, Hugo Larochelle, Joelle Pineau and Laurent Charlin
Predictive inference for travel time on transportation networks
Mohamad Elmasri, Aurelie Labbe, Denis Larocque and Laurent Charlin
arXiv: Methodology
(2020-04-23)
ui.adsabs.harvard.eduPDF
Prediction intervals for travel time on transportation networks
Mohamad Elmasri, Aurelie Labbe, Denis Larocque and Laurent Charlin
(venue unknown)
(2020-04-23)
Inference for travel time on transportation networks
Mohamad Elmasri, Aurelie Labbe, Denis Larocque and Laurent Charlin
arXiv preprint arXiv:2004.11292
(2020-04-23)
arxiv.org

2020-03

Online Fast Adaptation and Knowledge Accumulation: a New Approach to Continual Learning
Massimo Caccia, Pau Rodriguez, Oleksiy Ostapenko, Fabrice Normandin, Min Lin, Lucas Caccia, Issam Laradji, Irina Rish, Alexandre Lacoste, David Vazquez and Laurent Charlin
arXiv preprint arXiv:2003.05856
(2020-03-12)
export.arxiv.orgPDF

2020-01

Online Fast Adaptation and Knowledge Accumulation (OSAKA): a New Approach to Continual Learning
Massimo Caccia, Pau Rodriguez, Oleksiy Ostapenko, Fabrice Normandin, Min Lin, Lucas Page-Caccia, Issam Hadj Laradji, Irina Rish, Alexandre Lacoste, David Vázquez and Laurent Charlin
NEURIPS 2020
(2020-01-01)
papers.nips.ccPDF

2019-10

Continual Learning of New Sound Classes Using Generative Replay
Zhepei Wang, Cem Subakan, Efthymios Tzinis, Paris Smaragdis and Laurent Charlin

2019-08

Online Continual Learning with Maximally Interfered Retrieval.
Rahaf Aljundi, Lucas Caccia, Eugene Belilovsky, Massimo Caccia, Min Lin, Laurent Charlin and Tinne Tuytelaars
arXiv preprint arXiv:1908.04742
(2019-08-11)
export.arxiv.orgPDF

2019-01

Session-Based Social Recommendation via Dynamic Graph Attention Networks
Weiping Song, Zhiping Xiao, Yifan Wang, Laurent Charlin, Ming Zhang and Jian Tang
Online Continual Learning with Maximal Interfered Retrieval
Rahaf Aljundi, Eugene Belilovsky, Tinne Tuytelaars, Laurent Charlin, Massimo Caccia, Min Lin and Lucas Page-Caccia
NEURIPS 2019
(2019-01-01)
papers.nips.ccPDF
Exact Combinatorial Optimization with Graph Convolutional Neural Networks
Maxime Gasse, Didier Chetelat, Nicola Ferroni, Laurent Charlin and Andrea Lodi

2018-11

Towards Deep Conversational Recommendations
Raymond Li, Samira Ebrahimi Kahou, Hannes Schulz, Vincent Michalski, Laurent Charlin and Chris Pal

2018-07

Focused Hierarchical RNNs for Conditional Sequence Processing
Nan Rosemary Ke, Konrad Zolna, Alessandro Sordoni, Zhouhan Lin, Adam Trischler, Yoshua Bengio, Joelle Pineau, Laurent Charlin and Christopher J. Pal

2018-06

A Survey of Available Corpora For Building Data-Driven Dialogue Systems: The Journal Version
Iulian Vlad Serban, Ryan Lowe, Peter Henderson, Laurent Charlin and Joelle Pineau
Dialogue & Discourse
(2018-06-01)
dad.uni-bielefeld.de

2018-02

Sparse Attentive Backtracking: Long-Range Credit Assignment in Recurrent Networks
Nan Rosemary Ke, Anirudh Goyal, Olexa Bilaniuk, Jonathan Binas, Laurent Charlin, Chris Pal and Yoshua Bengio
arXiv preprint arXiv:1711.02326
(2018-02-15)
ui.adsabs.harvard.eduPDF

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