Laurent Charlin

Publication Activity (10 Years)

Years Active: 2006-2024
Publications (10 Years): 72

Top Topics

Dialogue System

Reinforcement Learning

Comparative Study

Top Venues

Publications

Yipeng Zhang, Laurent Charlin, Richard S. Zemel, Mengye Ren
Integrating Present and Past in Unsupervised Continual Learning. CoRR (2024)
Shubham Agarwal, Issam H. Laradji, Laurent Charlin, Christopher Pal
LitLLM: A Toolkit for Scientific Literature Review. CoRR (2024)
Oleksiy Ostapenko, Zhan Su, Edoardo Maria Ponti, Laurent Charlin, Nicolas Le Roux, Matheus Pereira, Lucas Caccia, Alessandro Sordoni
Towards Modular LLMs by Building and Reusing a Library of LoRAs. CoRR (2024)
Fotios Petropoulos, Gilbert Laporte, Emel Aktas, Sibel A. Alumur, Claudia Archetti, Hayriye Ayhan, Maria Battarra, Julia A. Bennell, Jean-Marie Bourjolly, John E. Boylan, Michèle Breton, David Canca, Laurent Charlin, Bo Chen, Cihan Tugrul Cicek, Louis Anthony Cox, Christine S. M. Currie, Erik Demeulemeester, Li Ding, Stephen M. Disney, Matthias Ehrgott, Martin J. Eppler, Günes Erdogan, Bernard Fortz, L. Alberto Franco, Jens Frische, Salvatore Greco, Amanda J. Gregory, Raimo P. Hämäläinen, Willy Herroelen, Mike Hewitt, Jan Holmström, John N. Hooker, Tugçe Isik, Jill Johnes, Bahar Yetis Kara, Özlem Karsu, Katherine Kent, Charlotte Köhler, Martin H. Kunc, Yong-Hong Kuo, Adam N. Letchford, Janny Leung, Dong Li, Haitao Li, Judit Lienert, Ivana Ljubic, Andrea Lodi, Sebastián Lozano, Virginie Lurkin, Silvano Martello, Ian G. McHale, Gerald Midgley, John D. W. Morecroft, Akshay Mutha, Ceyda Oguz, Sanja Petrovic, Ulrich Pferschy, Harilaos N. Psaraftis, Sam Rose, Lauri Saarinen, Saïd Salhi, Jing-Sheng Song, Dimitrios Sotiros, Kathryn E. Stecke, Arne K. Strauss, Istenç Tarhan, Clemens Thielen, Paolo Toth, Tom Van Woensel, Greet Vanden Berghe, Christos Vasilakis, Vikrant Vaze, Daniele Vigo, Kai Virtanen, Xun Wang, Rafal Weron, Leroy White, Mike Yearworth, E. Alper Yildirim, Georges Zaccour, Xuying Zhao
Operational Research: methods and applications. J. Oper. Res. Soc. 75 (3) (2024)
Tristan Deleu, Mizu Nishikawa-Toomey, Jithendaraa Subramanian, Nikolay Malkin, Laurent Charlin, Yoshua Bengio
Joint Bayesian Inference of Graphical Structure and Parameters with a Single Generative Flow Network. CoRR (2023)
Oleksiy Ostapenko, Pau Rodríguez, Alexandre Lacoste, Laurent Charlin
From IID to the Independent Mechanisms assumption in continual learning. AAAI Bridge Program (2023)
Timothée Lesort, Oleksiy Ostapenko, Pau Rodríguez, Diganta Misra, Md Rifat Arefin, Laurent Charlin, Irina Rish
Challenging Common Assumptions about Catastrophic Forgetting and Knowledge Accumulation. CoLLAs (2023)
Tianyu Shi, François-Xavier Devailly, Denis Larocque, Laurent Charlin
Improving the generalizability and robustness of large-scale traffic signal control. CoRR (2023)
Tristan Deleu, Mizu Nishikawa-Toomey, Jithendaraa Subramanian, Nikolay Malkin, Laurent Charlin, Yoshua Bengio
Joint Bayesian Inference of Graphical Structure and Parameters with a Single Generative Flow Network. NeurIPS (2023)
Massimo Caccia, Alexandre Galashov, Arthur Douillard, Amal Rannen-Triki, Dushyant Rao, Michela Paganini, Laurent Charlin, Marc'Aurelio Ranzato, Razvan Pascanu
Towards Compute-Optimal Transfer Learning. CoRR (2023)
Massimo Caccia, Jonas Mueller, Taesup Kim, Laurent Charlin, Rasool Fakoor
Task-Agnostic Continual Reinforcement Learning: Gaining Insights and Overcoming Challenges. CoLLAs (2023)
François-Xavier Devailly, Denis Larocque, Laurent Charlin
IG-RL: Inductive Graph Reinforcement Learning for Massive-Scale Traffic Signal Control. IEEE Trans. Intell. Transp. Syst. 23 (7) (2022)
Oleksiy Ostapenko, Timothée Lesort, Pau Rodríguez, Md Rifat Arefin, Arthur Douillard, Irina Rish, Laurent Charlin
Continual Learning with Foundation Models: An Empirical Study of Latent Replay. CoLLAs (2022)
Max B. Paulus, Giulia Zarpellon, Andreas Krause, Laurent Charlin, Chris J. Maddison
Learning To Cut By Looking Ahead: Cutting Plane Selection via Imitation Learning. CoRR (2022)
Timothée Lesort, Oleksiy Ostapenko, Diganta Misra, Md Rifat Arefin, Pau Rodríguez, Laurent Charlin, Irina Rish
Scaling the Number of Tasks in Continual Learning. CoRR (2022)
Massimo Caccia, Jonas Mueller, Taesup Kim, Laurent Charlin, Rasool Fakoor
Task-Agnostic Continual Reinforcement Learning: In Praise of a Simple Baseline. CoRR (2022)
François St-Hilaire, Dung Do Vu, Antoine Frau, Nathan Burns, Farid Faraji, Joseph Potochny, Stephane Robert, Arnaud Roussel, Selene Zheng, Taylor Glazier, Junfel Vincent Romano, Robert Belfer, Muhammad Shayan, Ariella Smofsky, Tommy Delarosbil, Seulmin Ahn, Simon Eden-Walker, Kritika Sony, Ansona Onyi Ching, Sabina Elkins, Anush Stepanyan, Adela Matajova, Victor Chen, Hossein Sahraei, Robert Larson, Nadia Markova, Andrew Barkett, Laurent Charlin, Yoshua Bengio, Iulian Vlad Serban, Ekaterina Kochmar
A New Era: Intelligent Tutoring Systems Will Transform Online Learning for Millions. CoRR (2022)
Mizu Nishikawa-Toomey, Tristan Deleu, Jithendaraa Subramanian, Yoshua Bengio, Laurent Charlin
Bayesian learning of Causal Structure and Mechanisms with GFlowNets and Variational Bayes. CoRR (2022)
Maxime Gasse, Quentin Cappart, Jonas Charfreitag, Laurent Charlin, Didier Chételat, Antonia Chmiela, Justin Dumouchelle, Ambros M. Gleixner, Aleksandr M. Kazachkov, Elias B. Khalil, Pawel Lichocki, Andrea Lodi, Miles Lubin, Chris J. Maddison, Christopher Morris, Dimitri J. Papageorgiou, Augustin Parjadis, Sebastian Pokutta, Antoine Prouvost, Lara Scavuzzo, Giulia Zarpellon, Linxin Yangm, Sha Lai, Akang Wang, Xiaodong Luo, Xiang Zhou, Haohan Huang, Sheng Cheng Shao, Yuanming Zhu, Dong Zhang, Tao Quan, Zixuan Cao, Yang Xu, Zhewei Huang, Shuchang Zhou, Chen Binbin, He Minggui, Hao Hao, Zhang Zhiyu, An Zhiwu, Mao Kun
The Machine Learning for Combinatorial Optimization Competition (ML4CO): Results and Insights. CoRR (2022)
François-Xavier Devailly, Denis Larocque, Laurent Charlin
Model-based graph reinforcement learning for inductive traffic signal control. CoRR (2022)
Oleksiy Ostapenko, Timothée Lesort, Pau Rodríguez, Md Rifat Arefin, Arthur Douillard, Irina Rish, Laurent Charlin
Foundational Models for Continual Learning: An Empirical Study of Latent Replay. CoRR (2022)
Max B. Paulus, Giulia Zarpellon, Andreas Krause, Laurent Charlin, Chris J. Maddison
Learning to Cut by Looking Ahead: Cutting Plane Selection via Imitation Learning. ICML (2022)
Pau Rodríguez, Massimo Caccia, Alexandre Lacoste, Lee Zamparo, Issam H. Laradji, Laurent Charlin, David Vázquez
Beyond Trivial Counterfactual Explanations with Diverse Valuable Explanations. CoRR (2021)
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, Ekaterina Kochmar
A Comparative Study of Learning Outcomes for Online Learning Platforms. AIED (2) (2021)
Pau Rodríguez, Massimo Caccia, Alexandre Lacoste, Lee Zamparo, Issam H. Laradji, Laurent Charlin, David Vázquez
Beyond Trivial Counterfactual Explanations with Diverse Valuable Explanations. ICCV (2021)
Oleksiy Ostapenko, Pau Rodríguez, Massimo Caccia, Laurent Charlin
Continual Learning via Local Module Composition. CoRR (2021)
Maxime Gasse, Simon Bowly, Quentin Cappart, Jonas Charfreitag, Laurent Charlin, Didier Chételat, Antonia Chmiela, Justin Dumouchelle, Ambros M. Gleixner, Aleksandr M. Kazachkov, Elias Khalil, Pawel Lichocki, Andrea Lodi, Miles Lubin, Chris J. Maddison, Christopher Morris, Dimitri J. Papageorgiou, Augustin Parjadis, Sebastian Pokutta, Antoine Prouvost, Lara Scavuzzo, Giulia Zarpellon, Linxin Yang, Sha Lai, Akang Wang, Xiaodong Luo, Xiang Zhou, Haohan Huang, Sheng Cheng Shao, Yuanming Zhu, Dong Zhang, Tao Quan, Zixuan Cao, Yang Xu, Zhewei Huang, Shuchang Zhou, Binbin Chen, Minggui He, Hao Hao, Zhiyu Zhang, Zhiwu An, Kun Mao
The Machine Learning for Combinatorial Optimization Competition (ML4CO): Results and Insights. NeurIPS (Competition and Demos) (2021)
Max Schwarzer, Nitarshan Rajkumar, Michael Noukhovitch, Ankesh Anand, Laurent Charlin, R. Devon Hjelm, Philip Bachman, Aaron C. Courville
Pretraining Representations for Data-Efficient Reinforcement Learning. CoRR (2021)
Max Schwarzer, Nitarshan Rajkumar, Michael Noukhovitch, Ankesh Anand, Laurent Charlin, R. Devon Hjelm, Philip Bachman, Aaron C. Courville
Pretraining Representations for Data-Efficient Reinforcement Learning. NeurIPS (2021)
Fabrice Normandin, Florian Golemo, Oleksiy Ostapenko, Pau Rodríguez, Matthew D. Riemer, Julio Hurtado, Khimya Khetarpal, Dominic Zhao, Ryan Lindeborg, Timothée Lesort, Laurent Charlin, Irina Rish, Massimo Caccia
Sequoia: A Software Framework to Unify Continual Learning Research. CoRR (2021)
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, Ekaterina Kochmar
Comparative Study of Learning Outcomes for Online Learning Platforms. CoRR (2021)
Oleksiy Ostapenko, Pau Rodríguez, Massimo Caccia, Laurent Charlin
Continual Learning via Local Module Composition. NeurIPS (2021)
Massimo Caccia, Pau Rodríguez, Oleksiy Ostapenko, Fabrice Normandin, Min Lin, Lucas Caccia, Issam H. Laradji, Irina Rish, Alexandre Lacoste, David Vázquez, Laurent Charlin
Online Fast Adaptation and Knowledge Accumulation: a New Approach to Continual Learning. CoRR (2020)
Yao Lu, Yue Dong, Laurent Charlin
Multi-XScience: A Large-scale Dataset for Extreme Multi-document Summarization of Scientific Articles. EMNLP (1) (2020)
Y. Cem Sübakan, Maxime Gasse, Laurent Charlin
On the Effectiveness of Two-Step Learning for Latent-Variable Models. MLSP (2020)
Massimo Caccia, Pau Rodríguez, Oleksiy Ostapenko, Fabrice Normandin, Min Lin, Lucas Page-Caccia, Issam Hadj Laradji, Irina Rish, Alexandre Lacoste, David Vázquez, Laurent Charlin
Online Fast Adaptation and Knowledge Accumulation (OSAKA): a New Approach to Continual Learning. NeurIPS (2020)
Alexandre Lacoste, Pau Rodríguez, Frédéric Branchaud-Charron, Parmida Atighehchian, Massimo Caccia, Issam H. Laradji, Alexandre Drouin, Matt Craddock, Laurent Charlin, David Vázquez
Synbols: Probing Learning Algorithms with Synthetic Datasets. CoRR (2020)
François-Xavier Devailly, Denis Larocque, Laurent Charlin
IG-RL: Inductive Graph Reinforcement Learning for Massive-Scale Traffic Signal Control. CoRR (2020)
Yao Lu, Yue Dong, Laurent Charlin
Multi-XScience: A Large-scale Dataset for Extreme Multi-document Summarization of Scientific Articles. CoRR (2020)
Iulian Vlad Serban, Varun Gupta, Ekaterina Kochmar, Dung Do Vu, Robert Belfer, Joelle Pineau, Aaron C. Courville, Laurent Charlin, Yoshua Bengio
A Large-Scale, Open-Domain, Mixed-Interface Dialogue-Based ITS for STEM. AIED (2) (2020)
Iulian Vlad Serban, Varun Gupta, Ekaterina Kochmar, Dung Do Vu, Robert Belfer, Joelle Pineau, Aaron C. Courville, Laurent Charlin, Yoshua Bengio
A Large-Scale, Open-Domain, Mixed-Interface Dialogue-Based ITS for STEM. CoRR (2020)
Massimo Caccia, Lucas Caccia, William Fedus, Hugo Larochelle, Joelle Pineau, Laurent Charlin
Language GANs Falling Short. ICLR (2020)
Yixin Wang, Dawen Liang, Laurent Charlin, David M. Blei
Causal Inference for Recommender Systems. RecSys (2020)
Alexandre Lacoste, Pau Rodríguez López, Frederic Branchaud-Charron, Parmida Atighehchian, Massimo Caccia, Issam Hadj Laradji, Alexandre Drouin, Matt Craddock, Laurent Charlin, David Vázquez
Synbols: Probing Learning Algorithms with Synthetic Datasets. NeurIPS (2020)
Maxime Gasse, Didier Chételat, Nicola Ferroni, Laurent Charlin, Andrea Lodi
Exact Combinatorial Optimization with Graph Convolutional Neural Networks. CoRR (2019)
Rahaf Aljundi, Eugene Belilovsky, Tinne Tuytelaars, Laurent Charlin, Massimo Caccia, Min Lin, Lucas Page-Caccia
Online Continual Learning with Maximal Interfered Retrieval. NeurIPS (2019)
Zhepei Wang, Y. Cem Sübakan, Efthymios Tzinis, Paris Smaragdis, Laurent Charlin
Continual Learning of New Sound Classes using Generative Replay. CoRR (2019)
Zhepei Wang, Y. Cem Sübakan, Efthymios Tzinis, Paris Smaragdis, Laurent Charlin
Continual Learning of New Sound Classes Using Generative Replay. WASPAA (2019)
Rahaf Aljundi, Lucas Caccia, Eugene Belilovsky, Massimo Caccia, Min Lin, Laurent Charlin, Tinne Tuytelaars
Online Continual Learning with Maximally Interfered Retrieval. CoRR (2019)
Weiping Song, Zhiping Xiao, Yifan Wang, Laurent Charlin, Ming Zhang, Jian Tang
Session-based Social Recommendation via Dynamic Graph Attention Networks. CoRR (2019)
Weiping Song, Zhiping Xiao, Yifan Wang, Laurent Charlin, Ming Zhang, Jian Tang
Session-Based Social Recommendation via Dynamic Graph Attention Networks. WSDM (2019)
Maxime Gasse, Didier Chételat, Nicola Ferroni, Laurent Charlin, Andrea Lodi
Exact Combinatorial Optimization with Graph Convolutional Neural Networks. NeurIPS (2019)
Yixin Wang, Dawen Liang, Laurent Charlin, David M. Blei
The Deconfounded Recommender: A Causal Inference Approach to Recommendation. CoRR (2018)
Nan Rosemary Ke, Konrad Zolna, Alessandro Sordoni, Zhouhan Lin, Adam Trischler, Yoshua Bengio, Joelle Pineau, Laurent Charlin, Christopher J. Pal
Focused Hierarchical RNNs for Conditional Sequence Processing. ICML (2018)
Raymond Li, Samira Ebrahimi Kahou, Hannes Schulz, Vincent Michalski, Laurent Charlin, Chris Pal
Towards Deep Conversational Recommendations. NeurIPS (2018)
Iulian Vlad Serban, Ryan Lowe, Peter Henderson, Laurent Charlin, Joelle Pineau
A Survey of Available Corpora For Building Data-Driven Dialogue Systems: The Journal Version. Dialogue Discourse 9 (1) (2018)
Massimo Caccia, Lucas Caccia, William Fedus, Hugo Larochelle, Joelle Pineau, Laurent Charlin
Language GANs Falling Short. CoRR (2018)
Nan Rosemary Ke, Konrad Zolna, Alessandro Sordoni, Zhouhan Lin, Adam Trischler, Yoshua Bengio, Joelle Pineau, Laurent Charlin, Chris Pal
Focused Hierarchical RNNs for Conditional Sequence Processing. CoRR (2018)
Raymond Li, Samira Ebrahimi Kahou, Hannes Schulz, Vincent Michalski, Laurent Charlin, Chris Pal
Towards Deep Conversational Recommendations. CoRR (2018)
Ryan Thomas Lowe, Nissan Pow, Iulian Vlad Serban, Laurent Charlin, Chia-Wei Liu, Joelle Pineau
Training End-to-End Dialogue Systems with the Ubuntu Dialogue Corpus. Dialogue Discourse 8 (1) (2017)
Chin-Wei Huang, Ahmed Touati, Laurent Dinh, Michal Drozdzal, Mohammad Havaei, Laurent Charlin, Aaron C. Courville
Learnable Explicit Density for Continuous Latent Space and Variational Inference. CoRR (2017)
Matthew Smith, Laurent Charlin, Joelle Pineau
A Sparse Probabilistic Model of User Preference Data. Canadian Conference on AI (2017)
Nan Rosemary Ke, Anirudh Goyal, Olexa Bilaniuk, Jonathan Binas, Laurent Charlin, Chris Pal, Yoshua Bengio
Sparse Attentive Backtracking: Long-Range Credit Assignment in Recurrent Networks. CoRR (2017)
Iulian Vlad Serban, Alessandro Sordoni, Ryan Lowe, Laurent Charlin, Joelle Pineau, Aaron C. Courville, Yoshua Bengio
A Hierarchical Latent Variable Encoder-Decoder Model for Generating Dialogues. AAAI (2017)
Dawen Liang, Laurent Charlin, James McInerney, David M. Blei
Modeling User Exposure in Recommendation. WWW (2016)
Dawen Liang, Jaan Altosaar, Laurent Charlin, David M. Blei
Factorization Meets the Item Embedding: Regularizing Matrix Factorization with Item Co-occurrence. RecSys (2016)
Iulian Vlad Serban, Ryan Lowe, Laurent Charlin, Joelle Pineau
Generative Deep Neural Networks for Dialogue: A Short Review. CoRR (2016)
Chia-Wei Liu, Ryan Lowe, Iulian Serban, Michael Noseworthy, Laurent Charlin, Joelle Pineau
How NOT To Evaluate Your Dialogue System: An Empirical Study of Unsupervised Evaluation Metrics for Dialogue Response Generation. EMNLP (2016)
Ryan Lowe, Iulian Vlad Serban, Michael Noseworthy, Laurent Charlin, Joelle Pineau
On the Evaluation of Dialogue Systems with Next Utterance Classification. SIGDIAL Conference (2016)
Ryan Lowe, Iulian Vlad Serban, Michael Noseworthy, Laurent Charlin, Joelle Pineau
On the Evaluation of Dialogue Systems with Next Utterance Classification. CoRR (2016)
Chia-Wei Liu, Ryan Lowe, Iulian Vlad Serban, Michael Noseworthy, Laurent Charlin, Joelle Pineau
How NOT To Evaluate Your Dialogue System: An Empirical Study of Unsupervised Evaluation Metrics for Dialogue Response Generation. CoRR (2016)
Iulian Vlad Serban, Alessandro Sordoni, Ryan Lowe, Laurent Charlin, Joelle Pineau, Aaron C. Courville, Yoshua Bengio
A Hierarchical Latent Variable Encoder-Decoder Model for Generating Dialogues. CoRR (2016)
Dawen Liang, Laurent Charlin, James McInerney, David M. Blei
Modeling User Exposure in Recommendation. CoRR (2015)
Iulian Vlad Serban, Ryan Lowe, Peter Henderson, Laurent Charlin, Joelle Pineau
A Survey of Available Corpora for Building Data-Driven Dialogue Systems. CoRR (2015)
Laurent Charlin, Rajesh Ranganath, James McInerney, David M. Blei
Dynamic Poisson Factorization. RecSys (2015)
Laurent Charlin, Rajesh Ranganath, James McInerney, David M. Blei
Dynamic Poisson Factorization. CoRR (2015)
Rajesh Ranganath, Linpeng Tang, Laurent Charlin, David M. Blei
Deep Exponential Families. AISTATS (2015)
Laurent Charlin, Richard S. Zemel, Hugo Larochelle
Leveraging user libraries to bootstrap collaborative filtering. KDD (2014)
Rajesh Ranganath, Linpeng Tang, Laurent Charlin, David M. Blei
Deep Exponential Families. CoRR (2014)
Prem Gopalan, Laurent Charlin, David M. Blei
Content-based recommendations with Poisson factorization. NIPS (2014)
Daniel Tarlow, Kevin Swersky, Laurent Charlin, Ilya Sutskever, Richard S. Zemel
Stochastic k-Neighborhood Selection for Supervised and Unsupervised Learning. ICML (3) (2013)
Laurent Charlin, Richard S. Zemel, Craig Boutilier
Active Learning for Matching Problems CoRR (2012)
Laurent Charlin, Richard S. Zemel, Craig Boutilier
Active Learning for Matching Problems. ICML (2012)
Laurent Charlin, Richard S. Zemel, Craig Boutilier
A Framework for Optimizing Paper Matching CoRR (2012)
Marc Toussaint, Laurent Charlin, Pascal Poupart
Hierarchical POMDP Controller Optimization by Likelihood Maximization CoRR (2012)
Laurent Charlin, Richard S. Zemel, Craig Boutilier
A Framework for Optimizing Paper Matching. UAI (2011)
Marc Toussaint, Laurent Charlin, Pascal Poupart
Hierarchical POMDP Controller Optimization by Likelihood Maximization. UAI (2008)
Laurent Charlin, Pascal Poupart, Romy Shioda
Automated Hierarchy Discovery for Planning in Partially Observable Environments. NIPS (2006)