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2020 – today
- 2024
[c10]Daniele Calandriello, Zhaohan Daniel Guo, Rémi Munos, Mark Rowland, Yunhao Tang, Bernardo Ávila Pires, Pierre Harvey Richemond, Charline Le Lan, Michal Valko, Tianqi Liu, Rishabh Joshi, Zeyu Zheng, Bilal Piot:
Human Alignment of Large Language Models through Online Preference Optimisation. ICML 2024- [i10]Daniele Calandriello, Daniel Guo, Rémi Munos, Mark Rowland, Yunhao Tang, Bernardo Ávila Pires, Pierre Harvey Richemond, Charline Le Lan, Michal Valko, Tianqi Liu, Rishabh Joshi, Zeyu Zheng, Bilal Piot:
Human Alignment of Large Language Models through Online Preference Optimisation. CoRR abs/2403.08635 (2024) - 2023
- [c9]Charline Le Lan, Joshua Greaves, Jesse Farebrother, Mark Rowland, Fabian Pedregosa, Rishabh Agarwal, Marc G. Bellemare:
A Novel Stochastic Gradient Descent Algorithm for Learning Principal Subspaces. AISTATS 2023: 1703-1718 - [c8]Jesse Farebrother, Joshua Greaves, Rishabh Agarwal, Charline Le Lan, Ross Goroshin, Pablo Samuel Castro, Marc G. Bellemare:
Proto-Value Networks: Scaling Representation Learning with Auxiliary Tasks. ICLR 2023 - [c7]Charline Le Lan, Rishabh Agarwal:
Revisiting Bisimulation: A Sampling-Based State Similarity Pseudo-metric. Tiny Papers @ ICLR 2023 - [c6]Charline Le Lan, Stephen Tu, Mark Rowland, Anna Harutyunyan, Rishabh Agarwal, Marc G. Bellemare, Will Dabney:
Bootstrapped Representations in Reinforcement Learning. ICML 2023: 18686-18713 - [c5]Yunhao Tang, Zhaohan Daniel Guo, Pierre Harvey Richemond, Bernardo Ávila Pires, Yash Chandak, Rémi Munos, Mark Rowland, Mohammad Gheshlaghi Azar, Charline Le Lan, Clare Lyle, András György, Shantanu Thakoor, Will Dabney, Bilal Piot, Daniele Calandriello, Michal Valko:
Understanding Self-Predictive Learning for Reinforcement Learning. ICML 2023: 33632-33656 - [i9]Jesse Farebrother, Joshua Greaves, Rishabh Agarwal, Charline Le Lan, Ross Goroshin, Pablo Samuel Castro, Marc G. Bellemare:
Proto-Value Networks: Scaling Representation Learning with Auxiliary Tasks. CoRR abs/2304.12567 (2023) - [i8]Charline Le Lan, Stephen Tu, Mark Rowland, Anna Harutyunyan, Rishabh Agarwal, Marc G. Bellemare, Will Dabney:
Bootstrapped Representations in Reinforcement Learning. CoRR abs/2306.10171 (2023) - 2022
- [c4]Charline Le Lan, Stephen Tu, Adam Oberman, Rishabh Agarwal, Marc G. Bellemare:
On the Generalization of Representations in Reinforcement Learning. AISTATS 2022: 4132-4157 - [i7]Charline Le Lan, Stephen Tu, Adam Oberman, Rishabh Agarwal, Marc G. Bellemare:
On the Generalization of Representations in Reinforcement Learning. CoRR abs/2203.00543 (2022) - [i6]Yunhao Tang, Zhaohan Daniel Guo, Pierre Harvey Richemond, Bernardo Ávila Pires, Yash Chandak, Rémi Munos, Mark Rowland, Mohammad Gheshlaghi Azar, Charline Le Lan, Clare Lyle, András György, Shantanu Thakoor, Will Dabney, Bilal Piot, Daniele Calandriello, Michal Valko:
Understanding Self-Predictive Learning for Reinforcement Learning. CoRR abs/2212.03319 (2022) - [i5]Charline Le Lan, Joshua Greaves, Jesse Farebrother, Mark Rowland, Fabian Pedregosa, Rishabh Agarwal, Marc G. Bellemare:
A Novel Stochastic Gradient Descent Algorithm for Learning Principal Subspaces. CoRR abs/2212.04025 (2022) - 2021
- [j1]Charline Le Lan, Laurent Dinh:
Perfect Density Models Cannot Guarantee Anomaly Detection. Entropy 23(12): 1690 (2021) - [c3]Charline Le Lan, Marc G. Bellemare, Pablo Samuel Castro:
Metrics and Continuity in Reinforcement Learning. AAAI 2021: 8261-8269 - [c2]Michael J. Hutchinson, Charline Le Lan, Sheheryar Zaidi, Emilien Dupont, Yee Whye Teh, Hyunjik Kim:
LieTransformer: Equivariant Self-Attention for Lie Groups. ICML 2021: 4533-4543 - [i4]Charline Le Lan, Marc G. Bellemare, Pablo Samuel Castro:
Metrics and continuity in reinforcement learning. CoRR abs/2102.01514 (2021) - 2020
- [i3]Charline Le Lan, Laurent Dinh:
Perfect density models cannot guarantee anomaly detection. CoRR abs/2012.03808 (2020) - [i2]Michael J. Hutchinson, Charline Le Lan, Sheheryar Zaidi, Emilien Dupont, Yee Whye Teh, Hyunjik Kim:
LieTransformer: Equivariant self-attention for Lie Groups. CoRR abs/2012.10885 (2020)
2010 – 2019
- 2019
- [c1]Emile Mathieu, Charline Le Lan, Chris J. Maddison, Ryota Tomioka, Yee Whye Teh:
Continuous Hierarchical Representations with Poincaré Variational Auto-Encoders. NeurIPS 2019: 12544-12555 - [i1]Emile Mathieu, Charline Le Lan, Chris J. Maddison, Ryota Tomioka, Yee Whye Teh:
Hierarchical Representations with Poincaré Variational Auto-Encoders. CoRR abs/1901.06033 (2019)
Coauthor Index
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