Charline Le Lan

21 papers A* 7A 2Journal 11Unranked 1

Year	Rank	Type	Title / Venue / Authors
2024	A*	`conf`	Human Alignment of Large Language Models through Online Preference Optimisation. ICML 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
2024	J	`jnl`	Human Alignment of Large Language Models through Online Preference Optimisation. CoRR 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
2023	A	`conf`	A Novel Stochastic Gradient Descent Algorithm for Learning Principal Subspaces. AISTATS Charline Le Lan, Joshua Greaves, Jesse Farebrother, Mark Rowland, Fabian Pedregosa, Rishabh Agarwal, Marc G. Bellemare
2023	A*	`conf`	Bootstrapped Representations in Reinforcement Learning. ICML Charline Le Lan, Stephen Tu, Mark Rowland, Anna Harutyunyan, Rishabh Agarwal, Marc G. Bellemare, Will Dabney
2023	J	`jnl`	Bootstrapped Representations in Reinforcement Learning. CoRR Charline Le Lan, Stephen Tu, Mark Rowland, Anna Harutyunyan, Rishabh Agarwal, Marc G. Bellemare, Will Dabney
2023	A*	`conf`	Proto-Value Networks: Scaling Representation Learning with Auxiliary Tasks. ICLR Jesse Farebrother, Joshua Greaves, Rishabh Agarwal, Charline Le Lan, Ross Goroshin, Pablo Samuel Castro, Marc G. Bellemare
2023	J	`jnl`	Proto-Value Networks: Scaling Representation Learning with Auxiliary Tasks. CoRR Jesse Farebrother, Joshua Greaves, Rishabh Agarwal, Charline Le Lan, Ross Goroshin, Pablo Samuel Castro, Marc G. Bellemare
2023	—	`conf`	Revisiting Bisimulation: A Sampling-Based State Similarity Pseudo-metric. Tiny Papers @ ICLR Charline Le Lan, Rishabh Agarwal
2023	A*	`conf`	Understanding Self-Predictive Learning for Reinforcement Learning. ICML 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
2022	J	`jnl`	A Novel Stochastic Gradient Descent Algorithm for Learning Principal Subspaces. CoRR Charline Le Lan, Joshua Greaves, Jesse Farebrother, Mark Rowland, Fabian Pedregosa, Rishabh Agarwal, Marc G. Bellemare
2022	A	`conf`	On the Generalization of Representations in Reinforcement Learning. AISTATS Charline Le Lan, Stephen Tu, Adam Oberman, Rishabh Agarwal, Marc G. Bellemare
2022	J	`jnl`	On the Generalization of Representations in Reinforcement Learning. CoRR Charline Le Lan, Stephen Tu, Adam Oberman, Rishabh Agarwal, Marc G. Bellemare
2022	J	`jnl`	Understanding Self-Predictive Learning for Reinforcement Learning. CoRR 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
2021	A*	`conf`	LieTransformer: Equivariant Self-Attention for Lie Groups. ICML Michael J. Hutchinson, Charline Le Lan, Sheheryar Zaidi, Emilien Dupont, Yee Whye Teh, Hyunjik Kim
2021	A*	`conf`	Metrics and Continuity in Reinforcement Learning. AAAI Charline Le Lan, Marc G. Bellemare, Pablo Samuel Castro
2021	J	`jnl`	Metrics and continuity in reinforcement learning. CoRR Charline Le Lan, Marc G. Bellemare, Pablo Samuel Castro
2021	J	`jnl`	Perfect Density Models Cannot Guarantee Anomaly Detection. Entropy Charline Le Lan, Laurent Dinh
2020	J	`jnl`	LieTransformer: Equivariant self-attention for Lie Groups. CoRR Michael J. Hutchinson, Charline Le Lan, Sheheryar Zaidi, Emilien Dupont, Yee Whye Teh, Hyunjik Kim
2020	J	`jnl`	Perfect density models cannot guarantee anomaly detection. CoRR Charline Le Lan, Laurent Dinh
2019	A*	`conf`	Continuous Hierarchical Representations with Poincaré Variational Auto-Encoders. NeurIPS Emile Mathieu, Charline Le Lan, Chris J. Maddison, Ryota Tomioka, Yee Whye Teh
2019	J	`jnl`	Hierarchical Representations with Poincaré Variational Auto-Encoders. CoRR Emile Mathieu, Charline Le Lan, Chris J. Maddison, Ryota Tomioka, Yee Whye Teh