Laurent Charlin

According to our database, Laurent Charlin authored at least 62 papers between 2006 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Operational Research: methods and applications.

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

J. Oper. Res. Soc., March, 2024

LitLLM: A Toolkit for Scientific Literature Review.

Shubham Agarwal, Issam H. Laradji, Laurent Charlin, Christopher Pal

CoRR, 2024

2023

Improving the generalizability and robustness of large-scale traffic signal control.

Tianyu Shi, François-Xavier Devailly, Denis Larocque, Laurent Charlin

CoRR, 2023

Towards Compute-Optimal Transfer Learning.

Massimo Caccia, Alexandre Galashov, Arthur Douillard, Amal Rannen-Triki, Dushyant Rao, Michela Paganini, Laurent Charlin, Marc'Aurelio Ranzato, Razvan Pascanu

CoRR, 2023

Joint Bayesian Inference of Graphical Structure and Parameters with a Single Generative Flow Network.

Tristan Deleu, Mizu Nishikawa-Toomey, Jithendaraa Subramanian, Nikolay Malkin, Laurent Charlin, Yoshua Bengio

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Challenging Common Assumptions about Catastrophic Forgetting and Knowledge Accumulation.

Timothée Lesort, Oleksiy Ostapenko, Pau Rodríguez, Diganta Misra, Md Rifat Arefin, Laurent Charlin, Irina Rish

Proceedings of the Conference on Lifelong Learning Agents, 2023

Task-Agnostic Continual Reinforcement Learning: Gaining Insights and Overcoming Challenges.

Massimo Caccia, Jonas Mueller, Taesup Kim, Laurent Charlin, Rasool Fakoor

Proceedings of the Conference on Lifelong Learning Agents, 2023

From IID to the Independent Mechanisms assumption in continual learning.

Oleksiy Ostapenko, Pau Rodríguez, Alexandre Lacoste, Laurent Charlin

Proceedings of the AAAI Bridge Program on Continual Causality, 2023

2022

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

François-Xavier Devailly, Denis Larocque, Laurent Charlin

IEEE Trans. Intell. Transp. Syst., 2022

Bayesian learning of Causal Structure and Mechanisms with GFlowNets and Variational Bayes.

Mizu Nishikawa-Toomey, Tristan Deleu, Jithendaraa Subramanian, Yoshua Bengio, Laurent Charlin

CoRR, 2022

Model-based graph reinforcement learning for inductive traffic signal control.

François-Xavier Devailly, Denis Larocque, Laurent Charlin

CoRR, 2022

Scaling the Number of Tasks in Continual Learning.

Timothée Lesort, Oleksiy Ostapenko, Diganta Misra, Md Rifat Arefin, Pau Rodríguez, Laurent Charlin, Irina Rish

CoRR, 2022

Task-Agnostic Continual Reinforcement Learning: In Praise of a Simple Baseline.

Massimo Caccia, Jonas Mueller, Taesup Kim, Laurent Charlin, Rasool Fakoor

CoRR, 2022

Foundational Models for Continual Learning: An Empirical Study of Latent Replay.

Oleksiy Ostapenko, Timothée Lesort, Pau Rodríguez, Md Rifat Arefin, Arthur Douillard, Irina Rish, Laurent Charlin

CoRR, 2022

A New Era: Intelligent Tutoring Systems Will Transform Online Learning for Millions.

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

CoRR, 2022

The Machine Learning for Combinatorial Optimization Competition (ML4CO): Results and Insights.

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 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

CoRR, 2022

Learning to Cut by Looking Ahead: Cutting Plane Selection via Imitation Learning.

Max B. Paulus, Giulia Zarpellon, Andreas Krause, Laurent Charlin, Chris J. Maddison

Proceedings of the International Conference on Machine Learning, 2022

Continual Learning with Foundation Models: An Empirical Study of Latent Replay.

Oleksiy Ostapenko, Timothée Lesort, Pau Rodríguez, Md Rifat Arefin, Arthur Douillard, Irina Rish, Laurent Charlin

Proceedings of the Conference on Lifelong Learning Agents, 2022

2021

Sequoia: A Software Framework to Unify Continual Learning Research.

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

CoRR, 2021

Pretraining Representations for Data-Efficient Reinforcement Learning.

Max Schwarzer, Nitarshan Rajkumar, Michael Noukhovitch, Ankesh Anand, Laurent Charlin, R. Devon Hjelm, Philip Bachman, Aaron C. Courville

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Continual Learning via Local Module Composition.

Oleksiy Ostapenko, Pau Rodríguez, Massimo Caccia, Laurent Charlin

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

The Machine Learning for Combinatorial Optimization Competition (ML4CO): Results and Insights.

Maxime Gasse, Simon Bowly, 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 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

Proceedings of the NeurIPS 2021 Competitions and Demonstrations Track, 2021

Beyond Trivial Counterfactual Explanations with Diverse Valuable Explanations.

Pau Rodríguez, Massimo Caccia, Alexandre Lacoste, Lee Zamparo, Issam H. Laradji, Laurent Charlin, David Vázquez

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

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, Ekaterina Kochmar

Proceedings of the Artificial Intelligence in Education - 22nd International Conference, 2021

2020

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

Massimo Caccia, Pau Rodríguez, Oleksiy Ostapenko, Fabrice Normandin, Min Lin, Lucas Caccia, Issam H. Laradji, Irina Rish, Alexandre Lacoste, David Vázquez, Laurent Charlin

CoRR, 2020

Causal Inference for Recommender Systems.

Yixin Wang, Dawen Liang, Laurent Charlin, David M. Blei

Proceedings of the RecSys 2020: Fourteenth ACM Conference on Recommender Systems, 2020

Synbols: Probing Learning Algorithms with Synthetic Datasets.

Alexandre Lacoste, Pau Rodríguez López, Frederic Branchaud-Charron, Parmida Atighehchian, Massimo Caccia, Issam Hadj Laradji, Alexandre Drouin, Matt Craddock, Laurent Charlin, David Vázquez

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Online Fast Adaptation and Knowledge Accumulation (OSAKA): a New Approach to Continual Learning.

Massimo Caccia, Pau Rodríguez, Oleksiy Ostapenko, Fabrice Normandin, Min Lin, Lucas Page-Caccia, Issam Hadj Laradji, Irina Rish, Alexandre Lacoste, David Vázquez, Laurent Charlin

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

On the Effectiveness of Two-Step Learning for Latent-Variable Models.

Y. Cem Sübakan, Maxime Gasse, Laurent Charlin

Proceedings of the 30th IEEE International Workshop on Machine Learning for Signal Processing, 2020

Language GANs Falling Short.

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

Proceedings of the 8th International Conference on Learning Representations, 2020

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

Yao Lu, Yue Dong, Laurent Charlin

Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

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, Yoshua Bengio

Proceedings of the Artificial Intelligence in Education - 21st International Conference, 2020

2019

Online Continual Learning with Maximally Interfered Retrieval.

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

CoRR, 2019

Session-Based Social Recommendation via Dynamic Graph Attention Networks.

Weiping Song, Zhiping Xiao, Yifan Wang, Laurent Charlin, Ming Zhang, Jian Tang

Proceedings of the Twelfth ACM International Conference on Web Search and Data Mining, 2019

Continual Learning of New Sound Classes Using Generative Replay.

Zhepei Wang, Y. Cem Sübakan, Efthymios Tzinis, Paris Smaragdis, Laurent Charlin

Proceedings of the 2019 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, 2019

Exact Combinatorial Optimization with Graph Convolutional Neural Networks.

Maxime Gasse, Didier Chételat, Nicola Ferroni, Laurent Charlin, Andrea Lodi

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Online Continual Learning with Maximal Interfered Retrieval.

Rahaf Aljundi, Eugene Belilovsky, Tinne Tuytelaars, Laurent Charlin, Massimo Caccia, Min Lin, Lucas Page-Caccia

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2018

A Survey of Available Corpora For Building Data-Driven Dialogue Systems: The Journal Version.

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

Dialogue Discourse, 2018

The Deconfounded Recommender: A Causal Inference Approach to Recommendation.

Yixin Wang, Dawen Liang, Laurent Charlin, David M. Blei

CoRR, 2018

Towards Deep Conversational Recommendations.

Raymond Li, Samira Ebrahimi Kahou, Hannes Schulz, Vincent Michalski, Laurent Charlin, Chris Pal

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Focused Hierarchical RNNs for Conditional Sequence Processing.

Nan Rosemary Ke, Konrad Zolna, Alessandro Sordoni, Zhouhan Lin, Adam Trischler, Yoshua Bengio, Joelle Pineau, Laurent Charlin, Christopher J. Pal

Proceedings of the 35th International Conference on Machine Learning, 2018

2017

Training End-to-End Dialogue Systems with the Ubuntu Dialogue Corpus.

Ryan Thomas Lowe, Nissan Pow, Iulian Vlad Serban, Laurent Charlin, Chia-Wei Liu, Joelle Pineau

Dialogue Discourse, 2017

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

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

CoRR, 2017

Learnable Explicit Density for Continuous Latent Space and Variational Inference.

Chin-Wei Huang, Ahmed Touati, Laurent Dinh, Michal Drozdzal, Mohammad Havaei, Laurent Charlin, Aaron C. Courville

CoRR, 2017

A Sparse Probabilistic Model of User Preference Data.

Matthew Smith, Laurent Charlin, Joelle Pineau

Proceedings of the Advances in Artificial Intelligence, 2017

A Hierarchical Latent Variable Encoder-Decoder Model for Generating Dialogues.

Iulian Vlad Serban, Alessandro Sordoni, Ryan Lowe, Laurent Charlin, Joelle Pineau, Aaron C. Courville, Yoshua Bengio

Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016

Generative Deep Neural Networks for Dialogue: A Short Review.

Iulian Vlad Serban, Ryan Lowe, Laurent Charlin, Joelle Pineau

CoRR, 2016

Modeling User Exposure in Recommendation.

Dawen Liang, Laurent Charlin, James McInerney, David M. Blei

Proceedings of the 25th International Conference on World Wide Web, 2016

On the Evaluation of Dialogue Systems with Next Utterance Classification.

Ryan Lowe, Iulian Vlad Serban, Michael D. Noseworthy, Laurent Charlin, Joelle Pineau

Proceedings of the SIGDIAL 2016 Conference, 2016

Factorization Meets the Item Embedding: Regularizing Matrix Factorization with Item Co-occurrence.

Dawen Liang, Jaan Altosaar, Laurent Charlin, David M. Blei

Proceedings of the 10th ACM Conference on Recommender Systems, 2016

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

Chia-Wei Liu, Ryan Lowe, Iulian Serban, Michael D. Noseworthy, Laurent Charlin, Joelle Pineau

Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing, 2016

2015

Supervised and Active Learning for Recommender Systems.

Laurent Charlin

PhD thesis, 2015

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

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

CoRR, 2015

Dynamic Poisson Factorization.

Laurent Charlin, Rajesh Ranganath, James McInerney, David M. Blei

Proceedings of the 9th ACM Conference on Recommender Systems, 2015

Deep Exponential Families.

Rajesh Ranganath, Linpeng Tang, Laurent Charlin, David M. Blei

Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

2014

Content-based recommendations with Poisson factorization.

Prem Gopalan, Laurent Charlin, David M. Blei

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Leveraging user libraries to bootstrap collaborative filtering.

Laurent Charlin, Richard S. Zemel, Hugo Larochelle

Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2014

2013

Stochastic k-Neighborhood Selection for Supervised and Unsupervised Learning.

Daniel Tarlow, Kevin Swersky, Laurent Charlin, Ilya Sutskever, Richard S. Zemel

Proceedings of the 30th International Conference on Machine Learning, 2013

2012

Active Learning for Matching Problems.

Laurent Charlin, Richard S. Zemel, Craig Boutilier

Proceedings of the 29th International Conference on Machine Learning, 2012

2011

A Framework for Optimizing Paper Matching.

Laurent Charlin, Richard S. Zemel, Craig Boutilier

Proceedings of the UAI 2011, 2011

2008

Hierarchical POMDP Controller Optimization by Likelihood Maximization.

Marc Toussaint, Laurent Charlin, Pascal Poupart

Proceedings of the UAI 2008, 2008

2006

Automated Hierarchy Discovery for Planning in Partially Observable Environments.

Laurent Charlin, Pascal Poupart, Romy Shioda

Proceedings of the Advances in Neural Information Processing Systems 19, 2006