Measuring the Carbon Intensity of AI in Cloud Instances
Remi Tachet des Combes, Erika Odmark, Will Buchanan
ACM Conference on Fairness, Accountability, and Transparency | June 2022
Return to Microsoft Research Lab – Montréal
Robust, adaptive, modular ML | Montréal
Publications
Publications
Publications par année
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A Deeper Look at Discounting Mismatch in Actor-Critic Algorithms
Shangtong Zhang, Romain Laroche, Harm van Seijen, Shimon Whiteson, Remi Tachet des Combes
International Conference on Autonomous Agents and Multiagent Systems (AAMAS) | May 2022
Better Language Model with Hypernym Class Prediction
He Bai, Tong Wang, Alessandro Sordoni, Peng Shi
ACL 2022 | May 2022
Unsupervised Dependency Graph Network
Yikang Shen, Shawn Tan, Alessandro Sordoni, Peng Li, Jie Zhou, Aaron Courville
ACL 2022 | May 2022
Evaluating Distributional Distortion in Neural Language Modeling
Benjamin LeBrun, Alessandro Sordoni, Timothy J. O’Donnell
ICLR 2022 | April 2022
Learning to Dequantise with Truncated Flows
Shawn Tan, Chin-Wei Huang, Alessandro Sordoni, Aaron Courville
ICLR 2022 | April 2022
Beyond the Policy Gradient Theorem for Efficient Policy Updates in Actor-Critic Algorithms
Romain Laroche, Remi Tachet des Combes
AISTATS 2022 | March 2022
A general class of surrogate functions for stable and efficient reinforcement learning
Sharan Vaswani, Olivier Bachem, Simone Totaro, Robert Müller, Shivam Garg, Matthieu Geist, Marlos C. Machado, Pablo Samuel Castro, Nicolas Le Roux
2022 International Conference on Artificial Intelligence and Statistics | March 2022
Collaborative Exploration and Exploitation in massively Multi-Player Bandits
Hiba Dakdouk, Raphaël Féraud, Nadège Varsier, Patrick Maillé, Romain Laroche
March 2022
On the Convergence of Stochastic Extragradient for Bilinear Games using Restarted Iteration Averaging
Chris Junchi Li, Yaodong Yu, Nicolas Loizou, Gauthier Gidel, Yi Ma, Nicolas Le Roux, Michael I. Jordan
2022 International Conference on Artificial Intelligence and Statistics | March 2022
On the Chattering of SARSA with Linear Function Approximation
Shangtong Zhang, Romain Laroche, Remi Tachet des Combes
February 2022
-
A single gradient step finds adversarial examples on random two-layers neural networks
Sébastien Bubeck, Yeshwanth Cherapanamjeri, Gauthier Gidel, Remi Tachet des Combes
NeurIPS 2021 | December 2021
Dr Jekyll & Mr Hyde: the strange case of off-policy policy updates
Romain Laroche, Remi Tachet des Combes
NeurIPS 2021 | December 2021
Pretraining Representations for Data-Efficient Reinforcement Learning
Max Schwarzer, Nitarshan Rajkumar, Michael Noukhovitch, Ankesh Anand, Laurent Charlin, Devon Hjelm, Philip Bachman, Aaron Courville
NeurIPS 2021 | December 2021
Self-training with Few-shot Rationalization: Teacher Explanations Aid Student in Few-shot NLU
Meghana Moorthy Bhat, Alessandro Sordoni, Subhabrata (Subho) Mukherjee
EMNLP 2021 | November 2021
The emergence of the shape bias results from communicative efficiency
Eva Portelance, Michael C. Frank, Dan Jurafsky, Alessandro Sordoni, Romain Laroche
Conference on Computational Natural Language Learning (CoNLL) | November 2021
Multi-Objective SPIBB: Seldonian Offline Policy Improvement with Safety Constraints in Finite MDPs
Harsh Satija, Philip S. Thomas, Joelle Pineau, Romain Laroche
2021 Neural Information Processing Systems | October 2021
Global Optimality and Finite Sample Analysis of Softmax Off-Policy Actor Critic under State Distribution Mismatch
Shangtong Zhang, Remi Tachet des Combes, Romain Laroche
October 2021
Batched Bandits with Crowd Externalities
Romain Laroche, Othmane Safsafi, Raphaël Féraud, Nicolas Broutin
September 2021
Decomposed Mutual Information Estimation for Contrastive Representation Learning
Alessandro Sordoni, Nouha Dziri, Hannes Schulz, Geoff Gordon, Philip Bachman, Remi Tachet des Combes
2021 International Conference on Machine Learning | July 2021
Bringing Structure into Summaries: a Faceted Summarization Dataset for Long Scientific Documents
Rui Meng, Khushboo Thaker, Lei Zhang, Yue Dong, Xingdi Yuan, Tong Wang, Daqing He
ACL-IJCNLP 2021 | May 2021
Explicitly Modeling Syntax in Language Models with Incremental Parsing and a Dynamic Oracle
Yikang Shen, Shawn Tan, Alessandro Sordoni, Siva Reddy, Aaron Courville
May 2021
Understanding by Understanding Not: Modeling Negation in Language Models
Arian Hosseini, Siva Reddy, Dzmitry Bahdanau, Devon Hjelm, Alessandro Sordoni, Aaron Courville
May 2021
Shortest-Path Constrained Reinforcement Learning for Sparse Reward Tasks
Sungryull Sohn, Sungtae Lee, Jongwook Choi, Harm van Seijen, Honglak Lee, Mehdi Fatemi
2021 International Conference on Machine Learning | May 2021
Learning to Represent Action Values as a Hypergraph on the Action Vertices
Arash Tavakoli, Mehdi Fatemi, Petar Kormushev
2021 International Conference on Learning Representations (ICLR’21) | May 2021
Linguistic dependencies and statistical dependence
Jacob Louis Hoover, Alessandro Sordoni, Wenyu Du, Timothy J. O’Donnell
2021 Empirical Methods in Natural Language Processing | April 2021
-
Domain Adaptation with Conditional Distribution Matching and Generalized Label Shift
Remi Tachet des Combes, Han Zhao, Yu-Xiang Wang, Geoff Gordon
NeurIPS | December 2020
Deep Reinforcement and InfoMax Learning
Bogdan Mazoure, Remi Tachet des Combes, Thang Long Doan, Philip Bachman, Devon Hjelm
NeurIPS 2020 | December 2020
Learning Dynamic Belief Graphs to Generalize on Text-Based Games
Ashutosh Adhikari, Xingdi Yuan, Marc-Alexandre Côté, Mikulas Zelinka, Marc-Antoine Rondeau, Romain Laroche, Pascal Poupart, Jian Tang, Adam Trischler, William L. Hamilton
NeurIPS 2020 | October 2020
Adversarial score matching and improved sampling for image generation
Alexia Jolicoeur-Martineau, Rémi Piché-Taillefer, Remi Tachet des Combes, Ioannis Mitliagkas
September 2020
Representation Learning with Video Deep InfoMax
Devon Hjelm, Philip Bachman
July 2020
Data-Efficient Reinforcement Learning with Momentum Predictive Representations
Max Schwarzer, Ankesh Anand, Rishab Goel, Devon Hjelm, Aaron Courville, Philip Bachman
July 2020
Reinforcement Learning Framework for Deep Brain Stimulation Study
Dmitrii Krylov, Remi Tachet des Combes, Romain Laroche, Michael Rosenblum, Dmitry V. Dylov
International Joint Conference on Artificial Intelligence | July 2020
A Reduction from Reinforcement Learning to No-Regret Online Learning
Ching-An Cheng, Remi Tachet des Combes, Byron Boots, Geoff Gordon
International Conference on Artificial Intelligence and Statistics | June 2020
Safe Policy Improvement with an Estimated Baseline Policy
Thiago D. Simao, Romain Laroche, Remi Tachet des Combes
International Conference on Autonomous Agents and Multi-Agent Systems | May 2020
Exploring and Predicting Transferability Across NLP Tasks
Tu Vu, Tong Wang, Tsendsuren Munkhdalai, Alessandro Sordoni, Adam Trischler, Andrew Mattarella-Micke, Subhransu Maji, Mohit Iyyer
May 2020
Fast Domain Adaptation For Goal-Oriented Dialogue Using A Hybrid Generative-Retrieval Transformer
Igor Shalyminov, Alessandro Sordoni, Adam Atkinson, Hannes Schulz
2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) | April 2020
Hybrid Generative-Retrieval Transformers For Dialogue Domain Adaptation
Igor Shalyminov, Alessandro Sordoni, Adam Atkinson, Hannes Schulz
arXiv preprint arXiv:2003.01680 | March 2020
Population Histories of the United States Revealed through Fine-Scale Migration and Haplotype Analysis
Chengzhen L. Dai, Mohammad M. Vazifeh, Chen-Hsiang Yeang, Remi Tachet des Combes, R. Spencer Wells, Miguel G. Vilar, Mark J. Daly, Carlo Ratti, Alicia R. Martin
The American Journal of Human Genetics | March 2020, Vol 106(3): pp. 371-388
-
Report on the First HIPstIR Workshop on the Future of Information Retrieval
Laura Dietz, Bhaskar Mitra, Jeremy Pickens, Hana Anber, Sandeep Avula, Asia J. Biega, Adrian Boteanu, Shubham Chatterjee, Jeff Dalton, Shiri Dori-Hacohen, John Foley, Henry Feild, Ben Gamari, Rosie Jones, Pallika Kanani, Sumanta Kashyapi, Widad Machmouchi, Matthew Mitsui, Steve Nole, Alexandre Tachard Passos, Jordan Ramsdell, Adam Roegiest, David Smith, Alessandro Sordoni
SIGIR Forum | December 2019, Vol 53(2): pp. 62-75
Using a Logarithmic Mapping to Enable Lower Discount Factors in Reinforcement Learning
Harm van Seijen, Mehdi Fatemi, Arash Tavakoli
Neural Information Processing Systems (NeurIPS) | December 2019
Oral Presentation
Ordered Memory
Yikang Shen, Shawn Tan, Arian Hosseini, Zhouhan Lin, Alessandro Sordoni, Aaron Courville
NeurIPS 2019 | November 2019
ArXiv
Robust Natural Language Inference Models with Example Forgetting
Yadollah Yaghoobzadeh, Remi Tachet des Combes, T. J. Hazen, Alessandro Sordoni
November 2019
Safe Policy Improvement with Soft Baseline Bootstrapping
Kimia Nadjahi, Romain Laroche, Remi Tachet des Combes
European Conference in Machine Learning (ECML-PKDD) | September 2019
Metalearned Neural Memory
Tsendsuren Munkhdalai, Alessandro Sordoni, Tong Wang, Adam Trischler
NeurIPS 2019 | July 2019
Preprint under review
Multi-batch Reinforcement Learning
Romain Laroche, Remi Tachet des Combes
The 4th Multidisciplinary Conference on Reinforcement Learning and Decision Making (RLDM) | July 2019
SPIBB-DQN: Safe Batch Reinforcement Learning with Function Approximation
Romain Laroche, Remi Tachet des Combes
The 4th Multidisciplinary Conference on Reinforcement Learning and Decision Making (RLDM) | July 2019
Learning Representations by Maximizing Mutual Information Across Views
Philip Bachman, Devon Hjelm, William Buchwalter
June 2019
Dead-ends and Secure Exploration in Reinforcement Learning
Mehdi Fatemi, Shikhar Sharma, Harm van Seijen, Samira Ebrahimi Kahou
Proceedings of the 36th International Conference on Machine Learning (ICML) | June 2019
Spotlight Presentation
On Learning Invariant Representation for Domain Adaptation
Han Zhao, Remi Tachet des Combes, Kun Zhang, Geoff Gordon
International Conference on Machine Learning | June 2019
On the Learning Dynamics of Deep Neural Networks
Remi Tachet des Combes
ICML – Theoretical Physics for Deep Learning Workshop | June 2019
Brief Report: Ordered Neurons: Integrating Tree Structures into Recurrent Neural Networks
Yikeng Shen, Shawn Tan, Alessandro Sordoni, Aaron Courville
ICLR 2019 | May 2019
ICLR 2019 Best Paper Award
An Empirical Study of Example Forgetting during Deep Neural Network Learning
Mariya Toneva, Alessandro Sordoni, Remi Tachet des Combes, Adam Trischler, Yoshua Bengio, Geoff Gordon
ICLR 2019 | April 2019
Learning deep representations by mutual information estimation and maximization
Devon Hjelm, Alex Fedorov, Samuel Lavoie-Marchildon, Karan Grewal, Philip Bachman, Adam Trischler, Yoshua Bengio
ICLR 2019 | April 2019
-
Towards Text Generation with Adversarially Learned Neural Outlines
Sandeep Subramanian, Sai Rajeswar, Alessandro Sordoni, Adam Trischler, Aaron Courville, Christopher Pal
NeurIPS 2018 | December 2018
Counting to Explore and Generalize in Text-based Games
Xingdi Yuan, Marc-Alexandre Côté, Alessandro Sordoni, Romain Laroche, Remi Tachet des Combes, Matthew Hausknecht, Adam Trischler
European Workshop on Reinforcement Learning (EWRL) | October 2018
Training Dialogue Systems With Human Advice
Merwan Barlier, Romain Laroche, Olivier Pietquin
Proceedings of the 17th International Conference on Autonomous Agents and Multiagent Systems (AAMAS) | July 2018
Straight to the Tree: Constituency Parsing with Neural Syntactic Distance
Yikang Shen, Zhouhan Lin, Athul Paul Jacob, Alessandro Sordoni, Aaron Courville, Yoshua Bengio
Proceedings of ACL | July 2018
Augmented cyclegan: Learning many-to-many mappings from unpaired data
Amjad Almahairi, Sai Rajeswar, Alessandro Sordoni, Philip Bachman, Aaron Courville
ICML 2018 | June 2018
ArXiv
Focused Hierarchical RNNs for Conditional Sequence Processing
Nan Rosemary Ke, Konrad Zolna, Alessandro Sordoni, Zhouhan Lin, Adam Trischler, Yoshua Bengio, Joelle Pineau, Laurent Charlin, Chris Pal
ICML 2018 | June 2018
In reinforcement learning, all objective functions are not equal
Romain Laroche, Harm van Seijen
Proceedings of the 6th International Conference on Learning Representations (ICLR) – workshop track | May 2018
Reinforcement Learning Algorithm Selection
Romain Laroche, Raphael Feraud
Proceedings of the 6th International Conference on Learning Representations (ICLR) | May 2018
On Value Function Representation of Long Horizon Problems
Lucas Lehnert, Romain Laroche, Harm van Seijen
Proceedings of the 33rd AAAI international conference | February 2018
Twin Networks: Matching the Future for Sequence Generation
Dmitriy Serdyuk, Nan Rosemary Ke, Alessandro Sordoni, Chris Pal, Adam Trischler, Yoshua Bengio
ICLR 2018 | January 2018
Filtre par zone de recherche
-
Measuring the Carbon Intensity of AI in Cloud Instances
Remi Tachet des Combes, Erika Odmark, Will Buchanan
ACM Conference on Fairness, Accountability, and Transparency | June 2022
A Deeper Look at Discounting Mismatch in Actor-Critic Algorithms
Shangtong Zhang, Romain Laroche, Harm van Seijen, Shimon Whiteson, Remi Tachet des Combes
International Conference on Autonomous Agents and Multiagent Systems (AAMAS) | May 2022
Learning to Dequantise with Truncated Flows
Shawn Tan, Chin-Wei Huang, Alessandro Sordoni, Aaron Courville
ICLR 2022 | April 2022
Evaluating Distributional Distortion in Neural Language Modeling
Benjamin LeBrun, Alessandro Sordoni, Timothy J. O’Donnell
ICLR 2022 | April 2022
Beyond the Policy Gradient Theorem for Efficient Policy Updates in Actor-Critic Algorithms
Romain Laroche, Remi Tachet des Combes
AISTATS 2022 | March 2022
Collaborative Exploration and Exploitation in massively Multi-Player Bandits
Hiba Dakdouk, Raphaël Féraud, Nadège Varsier, Patrick Maillé, Romain Laroche
March 2022
A general class of surrogate functions for stable and efficient reinforcement learning
Sharan Vaswani, Olivier Bachem, Simone Totaro, Robert Müller, Shivam Garg, Matthieu Geist, Marlos C. Machado, Pablo Samuel Castro, Nicolas Le Roux
2022 International Conference on Artificial Intelligence and Statistics | March 2022
On the Chattering of SARSA with Linear Function Approximation
Shangtong Zhang, Romain Laroche, Remi Tachet des Combes
February 2022
Dr Jekyll & Mr Hyde: the strange case of off-policy policy updates
Romain Laroche, Remi Tachet des Combes
NeurIPS 2021 | December 2021
Pretraining Representations for Data-Efficient Reinforcement Learning
Max Schwarzer, Nitarshan Rajkumar, Michael Noukhovitch, Ankesh Anand, Laurent Charlin, Devon Hjelm, Philip Bachman, Aaron Courville
NeurIPS 2021 | December 2021
A single gradient step finds adversarial examples on random two-layers neural networks
Sébastien Bubeck, Yeshwanth Cherapanamjeri, Gauthier Gidel, Remi Tachet des Combes
NeurIPS 2021 | December 2021
The emergence of the shape bias results from communicative efficiency
Eva Portelance, Michael C. Frank, Dan Jurafsky, Alessandro Sordoni, Romain Laroche
Conference on Computational Natural Language Learning (CoNLL) | November 2021
Multi-Objective SPIBB: Seldonian Offline Policy Improvement with Safety Constraints in Finite MDPs
Harsh Satija, Philip S. Thomas, Joelle Pineau, Romain Laroche
2021 Neural Information Processing Systems | October 2021
Global Optimality and Finite Sample Analysis of Softmax Off-Policy Actor Critic under State Distribution Mismatch
Shangtong Zhang, Remi Tachet des Combes, Romain Laroche
October 2021
Batched Bandits with Crowd Externalities
Romain Laroche, Othmane Safsafi, Raphaël Féraud, Nicolas Broutin
September 2021
Decomposed Mutual Information Estimation for Contrastive Representation Learning
Alessandro Sordoni, Nouha Dziri, Hannes Schulz, Geoff Gordon, Philip Bachman, Remi Tachet des Combes
2021 International Conference on Machine Learning | July 2021
Bringing Structure into Summaries: a Faceted Summarization Dataset for Long Scientific Documents
Rui Meng, Khushboo Thaker, Lei Zhang, Yue Dong, Xingdi Yuan, Tong Wang, Daqing He
ACL-IJCNLP 2021 | May 2021
Explicitly Modeling Syntax in Language Models with Incremental Parsing and a Dynamic Oracle
Yikang Shen, Shawn Tan, Alessandro Sordoni, Siva Reddy, Aaron Courville
May 2021
Understanding by Understanding Not: Modeling Negation in Language Models
Arian Hosseini, Siva Reddy, Dzmitry Bahdanau, Devon Hjelm, Alessandro Sordoni, Aaron Courville
May 2021
Shortest-Path Constrained Reinforcement Learning for Sparse Reward Tasks
Sungryull Sohn, Sungtae Lee, Jongwook Choi, Harm van Seijen, Honglak Lee, Mehdi Fatemi
2021 International Conference on Machine Learning | May 2021
Learning to Represent Action Values as a Hypergraph on the Action Vertices
Arash Tavakoli, Mehdi Fatemi, Petar Kormushev
2021 International Conference on Learning Representations (ICLR’21) | May 2021
Domain Adaptation with Conditional Distribution Matching and Generalized Label Shift
Remi Tachet des Combes, Han Zhao, Yu-Xiang Wang, Geoff Gordon
NeurIPS | December 2020
Deep Reinforcement and InfoMax Learning
Bogdan Mazoure, Remi Tachet des Combes, Thang Long Doan, Philip Bachman, Devon Hjelm
NeurIPS 2020 | December 2020
Learning Dynamic Belief Graphs to Generalize on Text-Based Games
Ashutosh Adhikari, Xingdi Yuan, Marc-Alexandre Côté, Mikulas Zelinka, Marc-Antoine Rondeau, Romain Laroche, Pascal Poupart, Jian Tang, Adam Trischler, William L. Hamilton
NeurIPS 2020 | October 2020
Data-Efficient Reinforcement Learning with Momentum Predictive Representations
Max Schwarzer, Ankesh Anand, Rishab Goel, Devon Hjelm, Aaron Courville, Philip Bachman
July 2020
Reinforcement Learning Framework for Deep Brain Stimulation Study
Dmitrii Krylov, Remi Tachet des Combes, Romain Laroche, Michael Rosenblum, Dmitry V. Dylov
International Joint Conference on Artificial Intelligence | July 2020
A Reduction from Reinforcement Learning to No-Regret Online Learning
Ching-An Cheng, Remi Tachet des Combes, Byron Boots, Geoff Gordon
International Conference on Artificial Intelligence and Statistics | June 2020
Safe Policy Improvement with an Estimated Baseline Policy
Thiago D. Simao, Romain Laroche, Remi Tachet des Combes
International Conference on Autonomous Agents and Multi-Agent Systems | May 2020
Hybrid Generative-Retrieval Transformers For Dialogue Domain Adaptation
Igor Shalyminov, Alessandro Sordoni, Adam Atkinson, Hannes Schulz
arXiv preprint arXiv:2003.01680 | March 2020
Report on the First HIPstIR Workshop on the Future of Information Retrieval
Laura Dietz, Bhaskar Mitra, Jeremy Pickens, Hana Anber, Sandeep Avula, Asia J. Biega, Adrian Boteanu, Shubham Chatterjee, Jeff Dalton, Shiri Dori-Hacohen, John Foley, Henry Feild, Ben Gamari, Rosie Jones, Pallika Kanani, Sumanta Kashyapi, Widad Machmouchi, Matthew Mitsui, Steve Nole, Alexandre Tachard Passos, Jordan Ramsdell, Adam Roegiest, David Smith, Alessandro Sordoni
SIGIR Forum | December 2019, Vol 53(2): pp. 62-75
Using a Logarithmic Mapping to Enable Lower Discount Factors in Reinforcement Learning
Harm van Seijen, Mehdi Fatemi, Arash Tavakoli
Neural Information Processing Systems (NeurIPS) | December 2019
Oral Presentation
Robust Natural Language Inference Models with Example Forgetting
Yadollah Yaghoobzadeh, Remi Tachet des Combes, T. J. Hazen, Alessandro Sordoni
November 2019
Ordered Memory
Yikang Shen, Shawn Tan, Arian Hosseini, Zhouhan Lin, Alessandro Sordoni, Aaron Courville
NeurIPS 2019 | November 2019
ArXiv
Safe Policy Improvement with Soft Baseline Bootstrapping
Kimia Nadjahi, Romain Laroche, Remi Tachet des Combes
European Conference in Machine Learning (ECML-PKDD) | September 2019
Metalearned Neural Memory
Tsendsuren Munkhdalai, Alessandro Sordoni, Tong Wang, Adam Trischler
NeurIPS 2019 | July 2019
Preprint under review
SPIBB-DQN: Safe Batch Reinforcement Learning with Function Approximation
Romain Laroche, Remi Tachet des Combes
The 4th Multidisciplinary Conference on Reinforcement Learning and Decision Making (RLDM) | July 2019
Multi-batch Reinforcement Learning
Romain Laroche, Remi Tachet des Combes
The 4th Multidisciplinary Conference on Reinforcement Learning and Decision Making (RLDM) | July 2019
Learning Representations by Maximizing Mutual Information Across Views
Philip Bachman, Devon Hjelm, William Buchwalter
June 2019
On the Learning Dynamics of Deep Neural Networks
Remi Tachet des Combes
ICML – Theoretical Physics for Deep Learning Workshop | June 2019
On Learning Invariant Representation for Domain Adaptation
Han Zhao, Remi Tachet des Combes, Kun Zhang, Geoff Gordon
International Conference on Machine Learning | June 2019
Dead-ends and Secure Exploration in Reinforcement Learning
Mehdi Fatemi, Shikhar Sharma, Harm van Seijen, Samira Ebrahimi Kahou
Proceedings of the 36th International Conference on Machine Learning (ICML) | June 2019
Spotlight Presentation
Brief Report: Ordered Neurons: Integrating Tree Structures into Recurrent Neural Networks
Yikeng Shen, Shawn Tan, Alessandro Sordoni, Aaron Courville
ICLR 2019 | May 2019
ICLR 2019 Best Paper Award
Learning deep representations by mutual information estimation and maximization
Devon Hjelm, Alex Fedorov, Samuel Lavoie-Marchildon, Karan Grewal, Philip Bachman, Adam Trischler, Yoshua Bengio
ICLR 2019 | April 2019
An Empirical Study of Example Forgetting during Deep Neural Network Learning
Mariya Toneva, Alessandro Sordoni, Remi Tachet des Combes, Adam Trischler, Yoshua Bengio, Geoff Gordon
ICLR 2019 | April 2019
Towards Text Generation with Adversarially Learned Neural Outlines
Sandeep Subramanian, Sai Rajeswar, Alessandro Sordoni, Adam Trischler, Aaron Courville, Christopher Pal
NeurIPS 2018 | December 2018
Counting to Explore and Generalize in Text-based Games
Xingdi Yuan, Marc-Alexandre Côté, Alessandro Sordoni, Romain Laroche, Remi Tachet des Combes, Matthew Hausknecht, Adam Trischler
European Workshop on Reinforcement Learning (EWRL) | October 2018
Training Dialogue Systems With Human Advice
Merwan Barlier, Romain Laroche, Olivier Pietquin
Proceedings of the 17th International Conference on Autonomous Agents and Multiagent Systems (AAMAS) | July 2018
Straight to the Tree: Constituency Parsing with Neural Syntactic Distance
Yikang Shen, Zhouhan Lin, Athul Paul Jacob, Alessandro Sordoni, Aaron Courville, Yoshua Bengio
Proceedings of ACL | July 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, Chris Pal
ICML 2018 | June 2018
Augmented cyclegan: Learning many-to-many mappings from unpaired data
Amjad Almahairi, Sai Rajeswar, Alessandro Sordoni, Philip Bachman, Aaron Courville
ICML 2018 | June 2018
ArXiv
In reinforcement learning, all objective functions are not equal
Romain Laroche, Harm van Seijen
Proceedings of the 6th International Conference on Learning Representations (ICLR) – workshop track | May 2018
Reinforcement Learning Algorithm Selection
Romain Laroche, Raphael Feraud
Proceedings of the 6th International Conference on Learning Representations (ICLR) | May 2018
On Value Function Representation of Long Horizon Problems
Lucas Lehnert, Romain Laroche, Harm van Seijen
Proceedings of the 33rd AAAI international conference | February 2018
Twin Networks: Matching the Future for Sequence Generation
Dmitriy Serdyuk, Nan Rosemary Ke, Alessandro Sordoni, Chris Pal, Adam Trischler, Yoshua Bengio
ICLR 2018 | January 2018
-
Measuring the Carbon Intensity of AI in Cloud Instances
Remi Tachet des Combes, Erika Odmark, Will Buchanan
ACM Conference on Fairness, Accountability, and Transparency | June 2022
-
Unsupervised Dependency Graph Network
Yikang Shen, Shawn Tan, Alessandro Sordoni, Peng Li, Jie Zhou, Aaron Courville
ACL 2022 | May 2022
Better Language Model with Hypernym Class Prediction
He Bai, Tong Wang, Alessandro Sordoni, Peng Shi
ACL 2022 | May 2022
Self-training with Few-shot Rationalization: Teacher Explanations Aid Student in Few-shot NLU
Meghana Moorthy Bhat, Alessandro Sordoni, Subhabrata (Subho) Mukherjee
EMNLP 2021 | November 2021
Bringing Structure into Summaries: a Faceted Summarization Dataset for Long Scientific Documents
Rui Meng, Khushboo Thaker, Lei Zhang, Yue Dong, Xingdi Yuan, Tong Wang, Daqing He
ACL-IJCNLP 2021 | May 2021
Understanding by Understanding Not: Modeling Negation in Language Models
Arian Hosseini, Siva Reddy, Dzmitry Bahdanau, Devon Hjelm, Alessandro Sordoni, Aaron Courville
May 2021
Linguistic dependencies and statistical dependence
Jacob Louis Hoover, Alessandro Sordoni, Wenyu Du, Timothy J. O’Donnell
2021 Empirical Methods in Natural Language Processing | April 2021
Exploring and Predicting Transferability Across NLP Tasks
Tu Vu, Tong Wang, Tsendsuren Munkhdalai, Alessandro Sordoni, Adam Trischler, Andrew Mattarella-Micke, Subhransu Maji, Mohit Iyyer
May 2020
-
On the Convergence of Stochastic Extragradient for Bilinear Games using Restarted Iteration Averaging
Chris Junchi Li, Yaodong Yu, Nicolas Loizou, Gauthier Gidel, Yi Ma, Nicolas Le Roux, Michael I. Jordan
2022 International Conference on Artificial Intelligence and Statistics | March 2022
-
A single gradient step finds adversarial examples on random two-layers neural networks
Sébastien Bubeck, Yeshwanth Cherapanamjeri, Gauthier Gidel, Remi Tachet des Combes
NeurIPS 2021 | December 2021
-
Adversarial score matching and improved sampling for image generation
Alexia Jolicoeur-Martineau, Rémi Piché-Taillefer, Remi Tachet des Combes, Ioannis Mitliagkas
September 2020
Representation Learning with Video Deep InfoMax
Devon Hjelm, Philip Bachman
July 2020
-
Population Histories of the United States Revealed through Fine-Scale Migration and Haplotype Analysis
Chengzhen L. Dai, Mohammad M. Vazifeh, Chen-Hsiang Yeang, Remi Tachet des Combes, R. Spencer Wells, Miguel G. Vilar, Mark J. Daly, Carlo Ratti, Alicia R. Martin
The American Journal of Human Genetics | March 2020, Vol 106(3): pp. 371-388
-
Fast Domain Adaptation For Goal-Oriented Dialogue Using A Hybrid Generative-Retrieval Transformer
Igor Shalyminov, Alessandro Sordoni, Adam Atkinson, Hannes Schulz
2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) | April 2020
-
Learning Dynamic Belief Graphs to Generalize on Text-Based Games
Ashutosh Adhikari, Xingdi Yuan, Marc-Alexandre Côté, Mikulas Zelinka, Marc-Antoine Rondeau, Romain Laroche, Pascal Poupart, Jian Tang, Adam Trischler, William L. Hamilton
NeurIPS 2020 | October 2020
-
Report on the First HIPstIR Workshop on the Future of Information Retrieval
Laura Dietz, Bhaskar Mitra, Jeremy Pickens, Hana Anber, Sandeep Avula, Asia J. Biega, Adrian Boteanu, Shubham Chatterjee, Jeff Dalton, Shiri Dori-Hacohen, John Foley, Henry Feild, Ben Gamari, Rosie Jones, Pallika Kanani, Sumanta Kashyapi, Widad Machmouchi, Matthew Mitsui, Steve Nole, Alexandre Tachard Passos, Jordan Ramsdell, Adam Roegiest, David Smith, Alessandro Sordoni
SIGIR Forum | December 2019, Vol 53(2): pp. 62-75
Publication Type
-
Measuring the Carbon Intensity of AI in Cloud Instances
Remi Tachet des Combes, Erika Odmark, Will Buchanan
ACM Conference on Fairness, Accountability, and Transparency | June 2022
Unsupervised Dependency Graph Network
Yikang Shen, Shawn Tan, Alessandro Sordoni, Peng Li, Jie Zhou, Aaron Courville
ACL 2022 | May 2022
Better Language Model with Hypernym Class Prediction
He Bai, Tong Wang, Alessandro Sordoni, Peng Shi
ACL 2022 | May 2022
A Deeper Look at Discounting Mismatch in Actor-Critic Algorithms
Shangtong Zhang, Romain Laroche, Harm van Seijen, Shimon Whiteson, Remi Tachet des Combes
International Conference on Autonomous Agents and Multiagent Systems (AAMAS) | May 2022
Learning to Dequantise with Truncated Flows
Shawn Tan, Chin-Wei Huang, Alessandro Sordoni, Aaron Courville
ICLR 2022 | April 2022
Evaluating Distributional Distortion in Neural Language Modeling
Benjamin LeBrun, Alessandro Sordoni, Timothy J. O’Donnell
ICLR 2022 | April 2022
Beyond the Policy Gradient Theorem for Efficient Policy Updates in Actor-Critic Algorithms
Romain Laroche, Remi Tachet des Combes
AISTATS 2022 | March 2022
On the Convergence of Stochastic Extragradient for Bilinear Games using Restarted Iteration Averaging
Chris Junchi Li, Yaodong Yu, Nicolas Loizou, Gauthier Gidel, Yi Ma, Nicolas Le Roux, Michael I. Jordan
2022 International Conference on Artificial Intelligence and Statistics | March 2022
A general class of surrogate functions for stable and efficient reinforcement learning
Sharan Vaswani, Olivier Bachem, Simone Totaro, Robert Müller, Shivam Garg, Matthieu Geist, Marlos C. Machado, Pablo Samuel Castro, Nicolas Le Roux
2022 International Conference on Artificial Intelligence and Statistics | March 2022
Dr Jekyll & Mr Hyde: the strange case of off-policy policy updates
Romain Laroche, Remi Tachet des Combes
NeurIPS 2021 | December 2021
Pretraining Representations for Data-Efficient Reinforcement Learning
Max Schwarzer, Nitarshan Rajkumar, Michael Noukhovitch, Ankesh Anand, Laurent Charlin, Devon Hjelm, Philip Bachman, Aaron Courville
NeurIPS 2021 | December 2021
A single gradient step finds adversarial examples on random two-layers neural networks
Sébastien Bubeck, Yeshwanth Cherapanamjeri, Gauthier Gidel, Remi Tachet des Combes
NeurIPS 2021 | December 2021
The emergence of the shape bias results from communicative efficiency
Eva Portelance, Michael C. Frank, Dan Jurafsky, Alessandro Sordoni, Romain Laroche
Conference on Computational Natural Language Learning (CoNLL) | November 2021
Self-training with Few-shot Rationalization: Teacher Explanations Aid Student in Few-shot NLU
Meghana Moorthy Bhat, Alessandro Sordoni, Subhabrata (Subho) Mukherjee
EMNLP 2021 | November 2021
Multi-Objective SPIBB: Seldonian Offline Policy Improvement with Safety Constraints in Finite MDPs
Harsh Satija, Philip S. Thomas, Joelle Pineau, Romain Laroche
2021 Neural Information Processing Systems | October 2021
Decomposed Mutual Information Estimation for Contrastive Representation Learning
Alessandro Sordoni, Nouha Dziri, Hannes Schulz, Geoff Gordon, Philip Bachman, Remi Tachet des Combes
2021 International Conference on Machine Learning | July 2021
Bringing Structure into Summaries: a Faceted Summarization Dataset for Long Scientific Documents
Rui Meng, Khushboo Thaker, Lei Zhang, Yue Dong, Xingdi Yuan, Tong Wang, Daqing He
ACL-IJCNLP 2021 | May 2021
Shortest-Path Constrained Reinforcement Learning for Sparse Reward Tasks
Sungryull Sohn, Sungtae Lee, Jongwook Choi, Harm van Seijen, Honglak Lee, Mehdi Fatemi
2021 International Conference on Machine Learning | May 2021
Learning to Represent Action Values as a Hypergraph on the Action Vertices
Arash Tavakoli, Mehdi Fatemi, Petar Kormushev
2021 International Conference on Learning Representations (ICLR’21) | May 2021
Linguistic dependencies and statistical dependence
Jacob Louis Hoover, Alessandro Sordoni, Wenyu Du, Timothy J. O’Donnell
2021 Empirical Methods in Natural Language Processing | April 2021
Domain Adaptation with Conditional Distribution Matching and Generalized Label Shift
Remi Tachet des Combes, Han Zhao, Yu-Xiang Wang, Geoff Gordon
NeurIPS | December 2020
Deep Reinforcement and InfoMax Learning
Bogdan Mazoure, Remi Tachet des Combes, Thang Long Doan, Philip Bachman, Devon Hjelm
NeurIPS 2020 | December 2020
Learning Dynamic Belief Graphs to Generalize on Text-Based Games
Ashutosh Adhikari, Xingdi Yuan, Marc-Alexandre Côté, Mikulas Zelinka, Marc-Antoine Rondeau, Romain Laroche, Pascal Poupart, Jian Tang, Adam Trischler, William L. Hamilton
NeurIPS 2020 | October 2020
Reinforcement Learning Framework for Deep Brain Stimulation Study
Dmitrii Krylov, Remi Tachet des Combes, Romain Laroche, Michael Rosenblum, Dmitry V. Dylov
International Joint Conference on Artificial Intelligence | July 2020
A Reduction from Reinforcement Learning to No-Regret Online Learning
Ching-An Cheng, Remi Tachet des Combes, Byron Boots, Geoff Gordon
International Conference on Artificial Intelligence and Statistics | June 2020
Safe Policy Improvement with an Estimated Baseline Policy
Thiago D. Simao, Romain Laroche, Remi Tachet des Combes
International Conference on Autonomous Agents and Multi-Agent Systems | May 2020
Fast Domain Adaptation For Goal-Oriented Dialogue Using A Hybrid Generative-Retrieval Transformer
Igor Shalyminov, Alessandro Sordoni, Adam Atkinson, Hannes Schulz
2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) | April 2020
Using a Logarithmic Mapping to Enable Lower Discount Factors in Reinforcement Learning
Harm van Seijen, Mehdi Fatemi, Arash Tavakoli
Neural Information Processing Systems (NeurIPS) | December 2019
Oral Presentation
Ordered Memory
Yikang Shen, Shawn Tan, Arian Hosseini, Zhouhan Lin, Alessandro Sordoni, Aaron Courville
NeurIPS 2019 | November 2019
ArXiv
Safe Policy Improvement with Soft Baseline Bootstrapping
Kimia Nadjahi, Romain Laroche, Remi Tachet des Combes
European Conference in Machine Learning (ECML-PKDD) | September 2019
Metalearned Neural Memory
Tsendsuren Munkhdalai, Alessandro Sordoni, Tong Wang, Adam Trischler
NeurIPS 2019 | July 2019
Preprint under review
SPIBB-DQN: Safe Batch Reinforcement Learning with Function Approximation
Romain Laroche, Remi Tachet des Combes
The 4th Multidisciplinary Conference on Reinforcement Learning and Decision Making (RLDM) | July 2019
Multi-batch Reinforcement Learning
Romain Laroche, Remi Tachet des Combes
The 4th Multidisciplinary Conference on Reinforcement Learning and Decision Making (RLDM) | July 2019
On the Learning Dynamics of Deep Neural Networks
Remi Tachet des Combes
ICML – Theoretical Physics for Deep Learning Workshop | June 2019
On Learning Invariant Representation for Domain Adaptation
Han Zhao, Remi Tachet des Combes, Kun Zhang, Geoff Gordon
International Conference on Machine Learning | June 2019
Dead-ends and Secure Exploration in Reinforcement Learning
Mehdi Fatemi, Shikhar Sharma, Harm van Seijen, Samira Ebrahimi Kahou
Proceedings of the 36th International Conference on Machine Learning (ICML) | June 2019
Spotlight Presentation
Brief Report: Ordered Neurons: Integrating Tree Structures into Recurrent Neural Networks
Yikeng Shen, Shawn Tan, Alessandro Sordoni, Aaron Courville
ICLR 2019 | May 2019
ICLR 2019 Best Paper Award
Learning deep representations by mutual information estimation and maximization
Devon Hjelm, Alex Fedorov, Samuel Lavoie-Marchildon, Karan Grewal, Philip Bachman, Adam Trischler, Yoshua Bengio
ICLR 2019 | April 2019
An Empirical Study of Example Forgetting during Deep Neural Network Learning
Mariya Toneva, Alessandro Sordoni, Remi Tachet des Combes, Adam Trischler, Yoshua Bengio, Geoff Gordon
ICLR 2019 | April 2019
Towards Text Generation with Adversarially Learned Neural Outlines
Sandeep Subramanian, Sai Rajeswar, Alessandro Sordoni, Adam Trischler, Aaron Courville, Christopher Pal
NeurIPS 2018 | December 2018
Counting to Explore and Generalize in Text-based Games
Xingdi Yuan, Marc-Alexandre Côté, Alessandro Sordoni, Romain Laroche, Remi Tachet des Combes, Matthew Hausknecht, Adam Trischler
European Workshop on Reinforcement Learning (EWRL) | October 2018
Training Dialogue Systems With Human Advice
Merwan Barlier, Romain Laroche, Olivier Pietquin
Proceedings of the 17th International Conference on Autonomous Agents and Multiagent Systems (AAMAS) | July 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, Chris Pal
ICML 2018 | June 2018
Augmented cyclegan: Learning many-to-many mappings from unpaired data
Amjad Almahairi, Sai Rajeswar, Alessandro Sordoni, Philip Bachman, Aaron Courville
ICML 2018 | June 2018
ArXiv
In reinforcement learning, all objective functions are not equal
Romain Laroche, Harm van Seijen
Proceedings of the 6th International Conference on Learning Representations (ICLR) – workshop track | May 2018
Reinforcement Learning Algorithm Selection
Romain Laroche, Raphael Feraud
Proceedings of the 6th International Conference on Learning Representations (ICLR) | May 2018
On Value Function Representation of Long Horizon Problems
Lucas Lehnert, Romain Laroche, Harm van Seijen
Proceedings of the 33rd AAAI international conference | February 2018
Twin Networks: Matching the Future for Sequence Generation
Dmitriy Serdyuk, Nan Rosemary Ke, Alessandro Sordoni, Chris Pal, Adam Trischler, Yoshua Bengio
ICLR 2018 | January 2018
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Collaborative Exploration and Exploitation in massively Multi-Player Bandits
Hiba Dakdouk, Raphaël Féraud, Nadège Varsier, Patrick Maillé, Romain Laroche
March 2022
On the Chattering of SARSA with Linear Function Approximation
Shangtong Zhang, Romain Laroche, Remi Tachet des Combes
February 2022
Global Optimality and Finite Sample Analysis of Softmax Off-Policy Actor Critic under State Distribution Mismatch
Shangtong Zhang, Remi Tachet des Combes, Romain Laroche
October 2021
Batched Bandits with Crowd Externalities
Romain Laroche, Othmane Safsafi, Raphaël Féraud, Nicolas Broutin
September 2021
Explicitly Modeling Syntax in Language Models with Incremental Parsing and a Dynamic Oracle
Yikang Shen, Shawn Tan, Alessandro Sordoni, Siva Reddy, Aaron Courville
May 2021
Understanding by Understanding Not: Modeling Negation in Language Models
Arian Hosseini, Siva Reddy, Dzmitry Bahdanau, Devon Hjelm, Alessandro Sordoni, Aaron Courville
May 2021
Adversarial score matching and improved sampling for image generation
Alexia Jolicoeur-Martineau, Rémi Piché-Taillefer, Remi Tachet des Combes, Ioannis Mitliagkas
September 2020
Representation Learning with Video Deep InfoMax
Devon Hjelm, Philip Bachman
July 2020
Data-Efficient Reinforcement Learning with Momentum Predictive Representations
Max Schwarzer, Ankesh Anand, Rishab Goel, Devon Hjelm, Aaron Courville, Philip Bachman
July 2020
Exploring and Predicting Transferability Across NLP Tasks
Tu Vu, Tong Wang, Tsendsuren Munkhdalai, Alessandro Sordoni, Adam Trischler, Andrew Mattarella-Micke, Subhransu Maji, Mohit Iyyer
May 2020
Robust Natural Language Inference Models with Example Forgetting
Yadollah Yaghoobzadeh, Remi Tachet des Combes, T. J. Hazen, Alessandro Sordoni
November 2019
Learning Representations by Maximizing Mutual Information Across Views
Philip Bachman, Devon Hjelm, William Buchwalter
June 2019
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Population Histories of the United States Revealed through Fine-Scale Migration and Haplotype Analysis
Chengzhen L. Dai, Mohammad M. Vazifeh, Chen-Hsiang Yeang, Remi Tachet des Combes, R. Spencer Wells, Miguel G. Vilar, Mark J. Daly, Carlo Ratti, Alicia R. Martin
The American Journal of Human Genetics | March 2020, Vol 106(3): pp. 371-388
Hybrid Generative-Retrieval Transformers For Dialogue Domain Adaptation
Igor Shalyminov, Alessandro Sordoni, Adam Atkinson, Hannes Schulz
arXiv preprint arXiv:2003.01680 | March 2020
Report on the First HIPstIR Workshop on the Future of Information Retrieval
Laura Dietz, Bhaskar Mitra, Jeremy Pickens, Hana Anber, Sandeep Avula, Asia J. Biega, Adrian Boteanu, Shubham Chatterjee, Jeff Dalton, Shiri Dori-Hacohen, John Foley, Henry Feild, Ben Gamari, Rosie Jones, Pallika Kanani, Sumanta Kashyapi, Widad Machmouchi, Matthew Mitsui, Steve Nole, Alexandre Tachard Passos, Jordan Ramsdell, Adam Roegiest, David Smith, Alessandro Sordoni
SIGIR Forum | December 2019, Vol 53(2): pp. 62-75
Straight to the Tree: Constituency Parsing with Neural Syntactic Distance
Yikang Shen, Zhouhan Lin, Athul Paul Jacob, Alessandro Sordoni, Aaron Courville, Yoshua Bengio
Proceedings of ACL | July 2018