Marc G. Bellemare

Publication record assembled from the DBLP archive of ranked conferences.

Papers indexed

Venues

Active years

2007–2024

Best venue rank

Where they publish

Papers

46 indexed papers, newest first.

Year	Venue	Title	Authors
2024	ICML	A Distributional Analogue to the Successor Representation.	Harley Wiltzer, Jesse Farebrother, Arthur Gretton, Yunhao Tang, Andr Barreto, Will Dabney, Marc G. Bellemare, Mark Rowland
2023	AISTATS	A Novel Stochastic Gradient Descent Algorithm for Learning Principal Subspaces.	Charline Le Lan, Joshua Greaves, Jesse Farebrother, Mark Rowland, Fabian Pedregosa, Rishabh Agarwal, Marc G. Bellemare
2023	ICLR	Sample-Efficient Reinforcement Learning by Breaking the Replay Ratio Barrier.	Pierluca D'Oro, Max Schwarzer, Evgenii Nikishin, Pierre-Luc Bacon, Marc G. Bellemare, Aaron C. Courville
2023	ICLR	Proto-Value Networks: Scaling Representation Learning with Auxiliary Tasks.	Jesse Farebrother, Joshua Greaves, Rishabh Agarwal, Charline Le Lan, Ross Goroshin, Pablo Samuel Castro, Marc G. Bellemare
2023	ICLR	The Small Batch Size Anomaly in Multistep Deep Reinforcement Learning.	Johan S. Obando-Ceron, Marc G. Bellemare, Pablo Samuel Castro
2023	ICLR	Investigating Multi-task Pretraining and Generalization in Reinforcement Learning.	Adrien Ali Taga, Rishabh Agarwal, Jesse Farebrother, Aaron C. Courville, Marc G. Bellemare
2023	ICML	Bootstrapped Representations in Reinforcement Learning.	Charline Le Lan, Stephen Tu, Mark Rowland, Anna Harutyunyan, Rishabh Agarwal, Marc G. Bellemare, Will Dabney
2023	ICML	The Statistical Benefits of Quantile Temporal-Difference Learning for Value Estimation.	Mark Rowland, Yunhao Tang, Clare Lyle, Rmi Munos, Marc G. Bellemare, Will Dabney
2023	ICML	Bigger, Better, Faster: Human-level Atari with human-level efficiency.	Max Schwarzer, Johan S. Obando-Ceron, Aaron C. Courville, Marc G. Bellemare, Rishabh Agarwal, Pablo Samuel Castro
2022	AISTATS	On the Generalization of Representations in Reinforcement Learning.	Charline Le Lan, Stephen Tu, Adam Oberman, Rishabh Agarwal, Marc G. Bellemare
2022	ICML	Distributional Hamilton-Jacobi-Bellman Equations for Continuous-Time Reinforcement Learning.	Harley E. Wiltzer, David Meger, Marc G. Bellemare
2021	AAAI	The Value-Improvement Path: Towards Better Representations for Reinforcement Learning.	Will Dabney, Andr Barreto, Mark Rowland, Robert Dadashi, John Quan, Marc G. Bellemare, David Silver
2021	AAAI	Metrics and Continuity in Reinforcement Learning.	Charline Le Lan, Marc G. Bellemare, Pablo Samuel Castro
2021	ICLR	Contrastive Behavioral Similarity Embeddings for Generalization in Reinforcement Learning.	Rishabh Agarwal, Marlos C. Machado, Pablo Samuel Castro, Marc G. Bellemare
2021	ICLR	The Importance of Pessimism in Fixed-Dataset Policy Optimization.	Jacob Buckman, Carles Gelada, Marc G. Bellemare
2020	AAAI	Algorithmic Improvements for Deep Reinforcement Learning Applied to Interactive Fiction.	Vishal Jain, William Fedus, Hugo Larochelle, Doina Precup, Marc G. Bellemare
2020	AAAI	Count-Based Exploration with the Successor Representation.	Marlos C. Machado, Marc G. Bellemare, Michael Bowling
2020	AISTATS	A Distributional Analysis of Sampling-Based Reinforcement Learning Algorithms.	Philip Amortila, Doina Precup, Prakash Panangaden, Marc G. Bellemare
2020	ICLR	On Bonus Based Exploration Methods In The Arcade Learning Environment.	Adrien Ali Taga, William Fedus, Marlos C. Machado, Aaron C. Courville, Marc G. Bellemare
2020	ICML	Representations for Stable Off-Policy Reinforcement Learning.	Dibya Ghosh, Marc G. Bellemare
2019	AAAI	Temporally Extended Metrics for Markov Decision Processes.	Philip Amortila, Marc G. Bellemare, Prakash Panangaden, Doina Precup
2019	AAAI	Off-Policy Deep Reinforcement Learning by Bootstrapping the Covariate Shift.	Carles Gelada, Marc G. Bellemare
2019	AAAI	A Comparative Analysis of Expected and Distributional Reinforcement Learning.	Clare Lyle, Marc G. Bellemare, Pablo Samuel Castro
2019	AISTATS	Distributional reinforcement learning with linear function approximation.	Marc G. Bellemare, Nicolas Le Roux, Pablo Samuel Castro, Subhodeep Moitra
2019	ICML	The Value Function Polytope in Reinforcement Learning.	Robert Dadashi, Marc G. Bellemare, Adrien Ali Taga, Nicolas Le Roux, Dale Schuurmans
2019	ICML	DeepMDP: Learning Continuous Latent Space Models for Representation Learning.	Carles Gelada, Saurabh Kumar, Jacob Buckman, Ofir Nachum, Marc G. Bellemare
2019	ICML	Statistics and Samples in Distributional Reinforcement Learning.	Mark Rowland, Robert Dadashi, Saurabh Kumar, Rmi Munos, Marc G. Bellemare, Will Dabney
2019	IJCAI	An Atari Model Zoo for Analyzing, Visualizing, and Comparing Deep Reinforcement Learning Agents.	Felipe Petroski Such, Vashisht Madhavan, Rosanne Liu, Rui Wang, Pablo Samuel Castro, Yulun Li, Jiale Zhi, Ludwig Schubert, Marc G. Bellemare, Jeff Clune, Joel Lehman
2018	AAAI	Distributional Reinforcement Learning With Quantile Regression.	Will Dabney, Mark Rowland, Marc G. Bellemare, Rmi Munos
2018	AISTATS	An Analysis of Categorical Distributional Reinforcement Learning.	Mark Rowland, Marc G. Bellemare, Will Dabney, Rmi Munos, Yee Whye Teh
2018	ICLR	The Reactor: A fast and sample-efficient Actor-Critic agent for Reinforcement Learning.	Audrunas Gruslys, Will Dabney, Mohammad Gheshlaghi Azar, Bilal Piot, Marc G. Bellemare, Rmi Munos
2018	IJCAI	Revisiting the Arcade Learning Environment: Evaluation Protocols and Open Problems for General Agents (Extended Abstract).	Marlos C. Machado, Marc G. Bellemare, Erik Talvitie, Joel Veness, Matthew J. Hausknecht, Michael Bowling
2017	ICML	A Distributional Perspective on Reinforcement Learning.	Marc G. Bellemare, Will Dabney, Rmi Munos
2017	ICML	Automated Curriculum Learning for Neural Networks.	Alex Graves, Marc G. Bellemare, Jacob Menick, Rmi Munos, Koray Kavukcuoglu
2017	ICML	A Laplacian Framework for Option Discovery in Reinforcement Learning.	Marlos C. Machado, Marc G. Bellemare, Michael H. Bowling
2017	ICML	Count-Based Exploration with Neural Density Models.	Georg Ostrovski, Marc G. Bellemare, Aron van den Oord, Rmi Munos
2016	AAAI	Increasing the Action Gap: New Operators for Reinforcement Learning.	Marc G. Bellemare, Georg Ostrovski, Arthur Guez, Philip S. Thomas, Rmi Munos
2016	ALT	Q(λ) with Off-Policy Corrections.	Anna Harutyunyan, Marc G. Bellemare, Tom Stepleton, Rmi Munos
2015	AAAI	Compress and Control.	Joel Veness, Marc G. Bellemare, Marcus Hutter, Alvin Chua, Guillaume Desjardins
2015	IJCAI	Count-Based Frequency Estimation with Bounded Memory.	Marc G. Bellemare
2015	IJCAI	The Arcade Learning Environment: An Evaluation Platform for General Agents (Extended Abstract).	Marc G. Bellemare, Yavar Naddaf, Joel Veness, Michael Bowling
2015	IJCAI	Online Learning of k-CNF Boolean Functions.	Joel Veness, Marcus Hutter, Laurent Orseau, Marc G. Bellemare
2014	ICML	Skip Context Tree Switching.	Marc G. Bellemare, Joel Veness, Erik Talvitie
2013	ICML	Bayesian Learning of Recursively Factored Environments.	Marc G. Bellemare, Joel Veness, Michael Bowling
2012	AAAI	Investigating Contingency Awareness Using Atari 2600 Games.	Marc G. Bellemare, Joel Veness, Michael Bowling
2007	IJCAI	Context-Driven Predictions.	Marc G. Bellemare, Doina Precup