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Deep Reinforcement Learning at the Edge of the Statistical Precipice

Aug 30, 2021
Rishabh Agarwal, Max Schwarzer, Pablo Samuel Castro, Aaron Courville, Marc G. Bellemare

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A functional mirror ascent view of policy gradient methods with function approximation

Aug 12, 2021
Sharan Vaswani, Olivier Bachem, Simone Totaro, Robert Mueller, Matthieu Geist, Marlos C. Machado, Pablo Samuel Castro, Nicolas Le Roux

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MICo: Learning improved representations via sampling-based state similarity for Markov decision processes

Jun 03, 2021
Pablo Samuel Castro, Tyler Kastner, Prakash Panangaden, Mark Rowland

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Metrics and continuity in reinforcement learning

Feb 02, 2021
Charline Le Lan, Marc G. Bellemare, Pablo Samuel Castro

* Accepted at AAAI 2021 

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Contrastive Behavioral Similarity Embeddings for Generalization in Reinforcement Learning

Jan 13, 2021
Rishabh Agarwal, Marlos C. Machado, Pablo Samuel Castro, Marc G. Bellemare

* Accepted at ICLR 2021 (Spotlight). Website: 

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Revisiting Rainbow: Promoting more insightful and inclusive deep reinforcement learning research

Nov 20, 2020
Johan S. Obando-Ceron, Pablo Samuel Castro

* Deep RL Workshop, NeurIPS 2020 

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Nov 06, 2020
Pablo Samuel Castro

* In 4th Workshop on Machine Learning for Creativity and Design at NeurIPS 2020, Vancouver, Canada 

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Rigging the Lottery: Making All Tickets Winners

Nov 25, 2019
Utku Evci, Trevor Gale, Jacob Menick, Pablo Samuel Castro, Erich Elsen

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Scalable methods for computing state similarity in deterministic Markov Decision Processes

Nov 21, 2019
Pablo Samuel Castro

* To appear in Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI-20) 

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Inverse Reinforcement Learning with Multiple Ranked Experts

Jul 31, 2019
Pablo Samuel Castro, Shijian Li, Daqing Zhang

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Performing Structured Improvisations with pre-trained Deep Learning Models

Apr 30, 2019
Pablo Samuel Castro

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A Comparative Analysis of Expected and Distributional Reinforcement Learning

Feb 21, 2019
Clare Lyle, Pablo Samuel Castro, Marc G. Bellemare

* To appear in the Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence 

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Distributional reinforcement learning with linear function approximation

Feb 08, 2019
Marc G. Bellemare, Nicolas Le Roux, Pablo Samuel Castro, Subhodeep Moitra

* Proceedings of AISTATS 2019 
* To appear 

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A Geometric Perspective on Optimal Representations for Reinforcement Learning

Jan 31, 2019
Marc G. Bellemare, Will Dabney, Robert Dadashi, Adrien Ali Taiga, Pablo Samuel Castro, Nicolas Le Roux, Dale Schuurmans, Tor Lattimore, Clare Lyle

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Shaping the Narrative Arc: An Information-Theoretic Approach to Collaborative Dialogue

Jan 31, 2019
Kory W. Mathewson, Pablo Samuel Castro, Colin Cherry, George Foster, Marc G. Bellemare

* 20 pages, 9 figures 

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An Atari Model Zoo for Analyzing, Visualizing, and Comparing Deep Reinforcement Learning Agents

Dec 17, 2018
Felipe Petroski Such, Vashisht Madhavan, Rosanne Liu, Rui Wang, Pablo Samuel Castro, Yulun Li, Ludwig Schubert, Marc Bellemare, Jeff Clune, Joel Lehman

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Dopamine: A Research Framework for Deep Reinforcement Learning

Dec 14, 2018
Pablo Samuel Castro, Subhodeep Moitra, Carles Gelada, Saurabh Kumar, Marc G. Bellemare

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Combining Learned Lyrical Structures and Vocabulary for Improved Lyric Generation

Nov 12, 2018
Pablo Samuel Castro, Maria Attarian

* Extended abstract (2 pages) for the NIPS 2018 Second Workshop on Machine Learning for Creativity and Design 

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Methods for computing state similarity in Markov Decision Processes

Jun 27, 2012
Norman Ferns, Pablo Samuel Castro, Doina Precup, Prakash Panangaden

* Appears in Proceedings of the Twenty-Second Conference on Uncertainty in Artificial Intelligence (UAI2006) 

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