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2020 – today
- 2024
[j4]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): 423-617 (2024)- [c40]Oleksiy Ostapenko, Zhan Su, Edoardo M. Ponti, Laurent Charlin, Nicolas Le Roux, Lucas Caccia, Alessandro Sordoni:
Towards Modular LLMs by Building and Reusing a Library of LoRAs. ICML 2024 - [i45]Shubham Agarwal, Issam H. Laradji, Laurent Charlin, Christopher Pal:
LitLLM: A Toolkit for Scientific Literature Review. CoRR abs/2402.01788 (2024) - [i44]Yipeng Zhang, Laurent Charlin, Richard S. Zemel, Mengye Ren:
Integrating Present and Past in Unsupervised Continual Learning. CoRR abs/2404.19132 (2024) - [i43]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 abs/2405.11157 (2024) - 2023
- [c39]Oleksiy Ostapenko, Pau Rodríguez, Alexandre Lacoste, Laurent Charlin:
From IID to the Independent Mechanisms assumption in continual learning. AAAI Bridge Program 2023: 25-29 - [c38]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: 43-65 - [c37]Massimo Caccia, Jonas Mueller, Taesup Kim, Laurent Charlin, Rasool Fakoor:
Task-Agnostic Continual Reinforcement Learning: Gaining Insights and Overcoming Challenges. CoLLAs 2023: 89-119 - [c36]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 - [i42]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 abs/2304.13164 (2023) - [i41]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 abs/2305.19366 (2023) - [i40]Tianyu Shi, François-Xavier Devailly, Denis Larocque, Laurent Charlin:
Improving the generalizability and robustness of large-scale traffic signal control. CoRR abs/2306.01925 (2023) - 2022
- [j3]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): 7496-7507 (2022) - [c35]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: 60-91 - [c34]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: 17584-17600 - [i39]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:
The Machine Learning for Combinatorial Optimization Competition (ML4CO): Results and Insights. CoRR abs/2203.02433 (2022) - [i38]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 abs/2203.03724 (2022) - [i37]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 abs/2205.00329 (2022) - [i36]Massimo Caccia, Jonas Mueller, Taesup Kim, Laurent Charlin, Rasool Fakoor:
Task-Agnostic Continual Reinforcement Learning: In Praise of a Simple Baseline. CoRR abs/2205.14495 (2022) - [i35]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 abs/2206.13414 (2022) - [i34]Timothée Lesort, Oleksiy Ostapenko, Diganta Misra, Md Rifat Arefin, Pau Rodríguez, Laurent Charlin, Irina Rish:
Scaling the Number of Tasks in Continual Learning. CoRR abs/2207.04543 (2022) - [i33]François-Xavier Devailly, Denis Larocque, Laurent Charlin:
Model-based graph reinforcement learning for inductive traffic signal control. CoRR abs/2208.00659 (2022) - [i32]Mizu Nishikawa-Toomey, Tristan Deleu, Jithendaraa Subramanian, Yoshua Bengio, Laurent Charlin:
Bayesian learning of Causal Structure and Mechanisms with GFlowNets and Variational Bayes. CoRR abs/2211.02763 (2022) - 2021
- [c33]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: 331-337 - [c32]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: 1036-1045 - [c31]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:
The Machine Learning for Combinatorial Optimization Competition (ML4CO): Results and Insights. NeurIPS (Competition and Demos) 2021: 220-231 - [c30]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: 12686-12699 - [c29]Oleksiy Ostapenko, Pau Rodríguez, Massimo Caccia, Laurent Charlin:
Continual Learning via Local Module Composition. NeurIPS 2021: 30298-30312 - [i31]Pau Rodríguez, Massimo Caccia, Alexandre Lacoste, Lee Zamparo, Issam H. Laradji, Laurent Charlin, David Vázquez:
Beyond Trivial Counterfactual Explanations with Diverse Valuable Explanations. CoRR abs/2103.10226 (2021) - [i30]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 abs/2104.07763 (2021) - [i29]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 abs/2106.04799 (2021) - [i28]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 abs/2108.01005 (2021) - [i27]Oleksiy Ostapenko, Pau Rodríguez, Massimo Caccia, Laurent Charlin:
Continual Learning via Local Module Composition. CoRR abs/2111.07736 (2021) - 2020
- [c28]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: 387-392 - [c27]Yao Lu, Yue Dong, Laurent Charlin:
Multi-XScience: A Large-scale Dataset for Extreme Multi-document Summarization of Scientific Articles. EMNLP (1) 2020: 8068-8074 - [c26]Massimo Caccia, Lucas Caccia, William Fedus, Hugo Larochelle, Joelle Pineau, Laurent Charlin:
Language GANs Falling Short. ICLR 2020 - [c25]Y. Cem Sübakan, Maxime Gasse, Laurent Charlin:
On the Effectiveness of Two-Step Learning for Latent-Variable Models. MLSP 2020: 1-6 - [c24]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 - [c23]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 - [c22]Yixin Wang, Dawen Liang, Laurent Charlin, David M. Blei:
Causal Inference for Recommender Systems. RecSys 2020: 426-431 - [i26]François-Xavier Devailly, Denis Larocque, Laurent Charlin:
IG-RL: Inductive Graph Reinforcement Learning for Massive-Scale Traffic Signal Control. CoRR abs/2003.05738 (2020) - [i25]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 abs/2003.05856 (2020) - [i24]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 abs/2005.06616 (2020) - [i23]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 abs/2009.06415 (2020) - [i22]Yao Lu, Yue Dong, Laurent Charlin:
Multi-XScience: A Large-scale Dataset for Extreme Multi-document Summarization of Scientific Articles. CoRR abs/2010.14235 (2020)
2010 – 2019
- 2019
- [c21]Rahaf Aljundi, Eugene Belilovsky, Tinne Tuytelaars, Laurent Charlin, Massimo Caccia, Min Lin, Lucas Page-Caccia:
Online Continual Learning with Maximal Interfered Retrieval. NeurIPS 2019: 11849-11860 - [c20]Maxime Gasse, Didier Chételat, Nicola Ferroni, Laurent Charlin, Andrea Lodi:
Exact Combinatorial Optimization with Graph Convolutional Neural Networks. NeurIPS 2019: 15554-15566 - [c19]Zhepei Wang, Y. Cem Sübakan, Efthymios Tzinis, Paris Smaragdis, Laurent Charlin:
Continual Learning of New Sound Classes Using Generative Replay. WASPAA 2019: 308-312 - [c18]Weiping Song, Zhiping Xiao, Yifan Wang, Laurent Charlin, Ming Zhang, Jian Tang:
Session-Based Social Recommendation via Dynamic Graph Attention Networks. WSDM 2019: 555-563 - [i21]Weiping Song, Zhiping Xiao, Yifan Wang, Laurent Charlin, Ming Zhang, Jian Tang:
Session-based Social Recommendation via Dynamic Graph Attention Networks. CoRR abs/1902.09362 (2019) - [i20]Zhepei Wang, Y. Cem Sübakan, Efthymios Tzinis, Paris Smaragdis, Laurent Charlin:
Continual Learning of New Sound Classes using Generative Replay. CoRR abs/1906.00654 (2019) - [i19]Maxime Gasse, Didier Chételat, Nicola Ferroni, Laurent Charlin, Andrea Lodi:
Exact Combinatorial Optimization with Graph Convolutional Neural Networks. CoRR abs/1906.01629 (2019) - [i18]Rahaf Aljundi, Lucas Caccia, Eugene Belilovsky, Massimo Caccia, Min Lin, Laurent Charlin, Tinne Tuytelaars:
Online Continual Learning with Maximally Interfered Retrieval. CoRR abs/1908.04742 (2019) - 2018
- [j2]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): 1-49 (2018) - [c17]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: 2559-2568 - [c16]Raymond Li, Samira Ebrahimi Kahou, Hannes Schulz, Vincent Michalski, Laurent Charlin, Chris Pal:
Towards Deep Conversational Recommendations. NeurIPS 2018: 9748-9758 - [i17]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 abs/1806.04342 (2018) - [i16]Yixin Wang, Dawen Liang, Laurent Charlin, David M. Blei:
The Deconfounded Recommender: A Causal Inference Approach to Recommendation. CoRR abs/1808.06581 (2018) - [i15]Massimo Caccia, Lucas Caccia, William Fedus, Hugo Larochelle, Joelle Pineau, Laurent Charlin:
Language GANs Falling Short. CoRR abs/1811.02549 (2018) - [i14]Raymond Li, Samira Ebrahimi Kahou, Hannes Schulz, Vincent Michalski, Laurent Charlin, Chris Pal:
Towards Deep Conversational Recommendations. CoRR abs/1812.07617 (2018) - 2017
- [j1]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): 31-65 (2017) - [c15]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: 3295-3301 - [c14]Matthew Smith, Laurent Charlin, Joelle Pineau:
A Sparse Probabilistic Model of User Preference Data. Canadian AI 2017: 316-328 - [i13]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 abs/1710.02248 (2017) - [i12]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 abs/1711.02326 (2017) - 2016
- [c13]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: 2122-2132 - [c12]Dawen Liang, Jaan Altosaar, Laurent Charlin, David M. Blei:
Factorization Meets the Item Embedding: Regularizing Matrix Factorization with Item Co-occurrence. RecSys 2016: 59-66 - [c11]Ryan Lowe, Iulian Vlad Serban, Michael Noseworthy, Laurent Charlin, Joelle Pineau:
On the Evaluation of Dialogue Systems with Next Utterance Classification. SIGDIAL Conference 2016: 264-269 - [c10]Dawen Liang, Laurent Charlin, James McInerney, David M. Blei:
Modeling User Exposure in Recommendation. WWW 2016: 951-961 - [i11]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 abs/1603.08023 (2016) - [i10]Ryan Lowe, Iulian Vlad Serban, Michael Noseworthy, Laurent Charlin, Joelle Pineau:
On the Evaluation of Dialogue Systems with Next Utterance Classification. CoRR abs/1605.05414 (2016) - [i9]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 abs/1605.06069 (2016) - [i8]Iulian Vlad Serban, Ryan Lowe, Laurent Charlin, Joelle Pineau:
Generative Deep Neural Networks for Dialogue: A Short Review. CoRR abs/1611.06216 (2016) - 2015
- [b1]Laurent Charlin:
Supervised and Active Learning for Recommender Systems. University of Toronto, Canada, 2015 - [c9]Rajesh Ranganath, Linpeng Tang, Laurent Charlin, David M. Blei:
Deep Exponential Families. AISTATS 2015 - [c8]Laurent Charlin, Rajesh Ranganath, James McInerney, David M. Blei:
Dynamic Poisson Factorization. RecSys 2015: 155-162 - [i7]Laurent Charlin, Rajesh Ranganath, James McInerney, David M. Blei:
Dynamic Poisson Factorization. CoRR abs/1509.04640 (2015) - [i6]Dawen Liang, Laurent Charlin, James McInerney, David M. Blei:
Modeling User Exposure in Recommendation. CoRR abs/1510.07025 (2015) - [i5]Iulian Vlad Serban, Ryan Lowe, Peter Henderson, Laurent Charlin, Joelle Pineau:
A Survey of Available Corpora for Building Data-Driven Dialogue Systems. CoRR abs/1512.05742 (2015) - 2014
- [c7]Laurent Charlin, Richard S. Zemel, Hugo Larochelle:
Leveraging user libraries to bootstrap collaborative filtering. KDD 2014: 173-182 - [c6]Prem Gopalan, Laurent Charlin, David M. Blei:
Content-based recommendations with Poisson factorization. NIPS 2014: 3176-3184 - [i4]Rajesh Ranganath, Linpeng Tang, Laurent Charlin, David M. Blei:
Deep Exponential Families. CoRR abs/1411.2581 (2014) - 2013
- [c5]Daniel Tarlow, Kevin Swersky, Laurent Charlin, Ilya Sutskever, Richard S. Zemel:
Stochastic k-Neighborhood Selection for Supervised and Unsupervised Learning. ICML (3) 2013: 199-207 - 2012
- [c4]Laurent Charlin, Richard S. Zemel, Craig Boutilier:
Active Learning for Matching Problems. ICML 2012 - [i3]Laurent Charlin, Richard S. Zemel, Craig Boutilier:
A Framework for Optimizing Paper Matching. CoRR abs/1202.3706 (2012) - [i2]Marc Toussaint, Laurent Charlin, Pascal Poupart:
Hierarchical POMDP Controller Optimization by Likelihood Maximization. CoRR abs/1206.3291 (2012) - [i1]Laurent Charlin, Richard S. Zemel, Craig Boutilier:
Active Learning for Matching Problems. CoRR abs/1206.4647 (2012) - 2011
- [c3]Laurent Charlin, Richard S. Zemel, Craig Boutilier:
A Framework for Optimizing Paper Matching. UAI 2011: 86-95
2000 – 2009
- 2008
- [c2]Marc Toussaint, Laurent Charlin, Pascal Poupart:
Hierarchical POMDP Controller Optimization by Likelihood Maximization. UAI 2008: 562-570 - 2006
- [c1]Laurent Charlin, Pascal Poupart, Romy Shioda:
Automated Hierarchy Discovery for Planning in Partially Observable Environments. NIPS 2006: 225-232
Coauthor Index
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