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Continual Learning via Local Module Composition

Nov 15, 2021
Oleksiy Ostapenko, Pau Rodriguez, Massimo Caccia, Laurent Charlin

* NeurIPS 2021 

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Sequoia: A Software Framework to Unify Continual Learning Research

Aug 03, 2021
Fabrice Normandin, Florian Golemo, Oleksiy Ostapenko, Pau Rodriguez, Matthew D Riemer, Julio Hurtado, Khimya Khetarpal, Dominic Zhao, Ryan Lindeborg, Timothée Lesort, Laurent Charlin, Irina Rish, Massimo Caccia

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Pretraining Representations for Data-Efficient Reinforcement Learning

Jun 09, 2021
Max Schwarzer, Nitarshan Rajkumar, Michael Noukhovitch, Ankesh Anand, Laurent Charlin, Devon Hjelm, Philip Bachman, Aaron Courville

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Comparative Study of Learning Outcomes for Online Learning Platforms

Apr 15, 2021
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, Ekaterina Kochmar

* 14 pages, 3 figures, 2 tables, accepted at AIED 2021 (2021 Conference on Artificial Intelligence in Education) 

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Beyond Trivial Counterfactual Explanations with Diverse Valuable Explanations

Mar 18, 2021
Pau Rodriguez, Massimo Caccia, Alexandre Lacoste, Lee Zamparo, Issam Laradji, Laurent Charlin, David Vazquez

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Multi-XScience: A Large-scale Dataset for Extreme Multi-document Summarization of Scientific Articles

Oct 27, 2020
Yao Lu, Yue Dong, Laurent Charlin

* EMNLP 2020 

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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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A Large-Scale, Open-Domain, Mixed-Interface Dialogue-Based ITS for STEM

May 06, 2020
Iulian Vlad Serban, Varun Gupta, Ekaterina Kochmar, Dung D. Vu, Robert Belfer, Joelle Pineau, Aaron Courville, Laurent Charlin, Yoshua Bengio

* 6 pages, 1 figure, 1 table, accepted for publication in the 21st International Conference on Artificial Intelligence in Education (AIED 2020) 

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IG-RL: Inductive Graph Reinforcement Learning for Massive-Scale Traffic Signal Control

Mar 19, 2020
François-Xavier Devailly, Denis Larocque, Laurent Charlin

* 11 pages, 9 figures, 1 table 

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Online Fast Adaptation and Knowledge Accumulation: a New Approach to Continual Learning

Mar 12, 2020
Massimo Caccia, Pau Rodriguez, Oleksiy Ostapenko, Fabrice Normandin, Min Lin, Lucas Caccia, Issam Laradji, Irina Rish, Alexande Lacoste, David Vazquez, Laurent Charlin

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Online Continual Learning with Maximally Interfered Retrieval

Aug 23, 2019
Rahaf Aljundi, Lucas Caccia, Eugene Belilovsky, Massimo Caccia, Min Lin, Laurent Charlin, Tinne Tuytelaars

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Exact Combinatorial Optimization with Graph Convolutional Neural Networks

Jun 07, 2019
Maxime Gasse, Didier Chételat, Nicola Ferroni, Laurent Charlin, Andrea Lodi

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Continual Learning of New Sound Classes using Generative Replay

Jun 03, 2019
Zhepei Wang, Cem Subakan, Efthymios Tzinis, Paris Smaragdis, Laurent Charlin

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Towards Deep Conversational Recommendations

Dec 18, 2018
Raymond Li, Samira Kahou, Hannes Schulz, Vincent Michalski, Laurent Charlin, Chris Pal

* 17 pages, 5 figures, Accepted at 32nd Conference on Neural Information Processing Systems (NeurIPS 2018), Montr\'eal, Canada 

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Language GANs Falling Short

Nov 08, 2018
Massimo Caccia, Lucas Caccia, William Fedus, Hugo Larochelle, Joelle Pineau, Laurent Charlin

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The Deconfounded Recommender: A Causal Inference Approach to Recommendation

Aug 20, 2018
Yixin Wang, Dawen Liang, Laurent Charlin, David M. Blei

* 14 pages, 3 figures 

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Focused Hierarchical RNNs for Conditional Sequence Processing

Jun 12, 2018
Nan Rosemary Ke, Konrad Zolna, Alessandro Sordoni, Zhouhan Lin, Adam Trischler, Yoshua Bengio, Joelle Pineau, Laurent Charlin, Chris Pal

* To appear at ICML 2018 

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Sparse Attentive Backtracking: Long-Range Credit Assignment in Recurrent Networks

Nov 07, 2017
Nan Rosemary Ke, Anirudh Goyal, Olexa Bilaniuk, Jonathan Binas, Laurent Charlin, Chris Pal, Yoshua Bengio

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Learnable Explicit Density for Continuous Latent Space and Variational Inference

Oct 06, 2017
Chin-Wei Huang, Ahmed Touati, Laurent Dinh, Michal Drozdzal, Mohammad Havaei, Laurent Charlin, Aaron Courville

* 2 figures, 5 pages, submitted to ICML Principled Approaches to Deep Learning workshop 

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A Survey of Available Corpora for Building Data-Driven Dialogue Systems

Mar 21, 2017
Iulian Vlad Serban, Ryan Lowe, Peter Henderson, Laurent Charlin, Joelle Pineau

* 56 pages including references and appendix, 5 tables and 1 figure; Under review for the Dialogue & Discourse journal. Update: paper has been rewritten and now includes several new datasets 

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How NOT To Evaluate Your Dialogue System: An Empirical Study of Unsupervised Evaluation Metrics for Dialogue Response Generation

Jan 03, 2017
Chia-Wei Liu, Ryan Lowe, Iulian V. Serban, Michael Noseworthy, Laurent Charlin, Joelle Pineau

* First 4 authors had equal contribution. 13 pages, 5 tables, 6 figures. EMNLP 2016 

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Generative Deep Neural Networks for Dialogue: A Short Review

Nov 18, 2016
Iulian Vlad Serban, Ryan Lowe, Laurent Charlin, Joelle Pineau

* 6 pages, 1 figure, 3 tables; NIPS 2016 workshop on Learning Methods for Dialogue 

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On the Evaluation of Dialogue Systems with Next Utterance Classification

Jul 23, 2016
Ryan Lowe, Iulian V. Serban, Mike Noseworthy, Laurent Charlin, Joelle Pineau

* Accepted to SIGDIAL 2016 (short paper). 5 pages 

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A Hierarchical Latent Variable Encoder-Decoder Model for Generating Dialogues

Jun 14, 2016
Iulian Vlad Serban, Alessandro Sordoni, Ryan Lowe, Laurent Charlin, Joelle Pineau, Aaron Courville, Yoshua Bengio

* 15 pages, 5 tables, 4 figures 

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Modeling User Exposure in Recommendation

Feb 04, 2016
Dawen Liang, Laurent Charlin, James McInerney, David M. Blei

* 11 pages, 4 figures. WWW'16 

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Dynamic Poisson Factorization

Sep 15, 2015
Laurent Charlin, Rajesh Ranganath, James McInerney, David M. Blei

* RecSys 2015 

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