Max Schwarzer

TalkRL: The Reinforcement Learning Podcast

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1+ y ago 1:10:18

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Max Schwarzer is a PhD student at Mila, with Aaron Courville and Marc Bellemare, interested in RL scaling, representation learning for RL, and RL for science. Max spent the last 1.5 years at Google Brain/DeepMind, and is now at Apple Machine Learning Research.

Featured References

Bigger, Better, Faster: Human-level Atari with human-level efficiency
Max Schwarzer, Johan Obando-Ceron, Aaron Courville, Marc Bellemare, Rishabh Agarwal, Pablo Samuel Castro

Sample-Efficient Reinforcement Learning by Breaking the Replay Ratio Barrier
Pierluca D'Oro, Max Schwarzer, Evgenii Nikishin, Pierre-Luc Bacon, Marc G Bellemare, Aaron Courville
The Primacy Bias in Deep Reinforcement Learning
Evgenii Nikishin, Max Schwarzer, Pierluca D'Oro, Pierre-Luc Bacon, Aaron Courville

Additional References

Rainbow: Combining Improvements in Deep Reinforcement Learning, Hessel et al 2017
When to use parametric models in reinforcement learning? Hasselt et al 2019
Data-Efficient Reinforcement Learning with Self-Predictive Representations, Schwarzer et al 2020
Pretraining Representations for Data-Efficient Reinforcement Learning, Schwarzer et al 2021

66 episodes

#Reinforcement Learning #Machine Learning #Robin Ranjit Singh Chauhan #Artificial Intelligence #Tech

Max Schwarzer

TalkRL: The Reinforcement Learning Podcast

89 subscribers

published 1+ y ago

MP3•Episode home

Rainbow: Combining Improvements in Deep Reinforcement Learning, Hessel et al 2017
When to use parametric models in reinforcement learning? Hasselt et al 2019
Data-Efficient Reinforcement Learning with Self-Predictive Representations, Schwarzer et al 2020
Pretraining Representations for Data-Efficient Reinforcement Learning, Schwarzer et al 2021

66 episodes

#Reinforcement Learning #Machine Learning #Robin Ranjit Singh Chauhan #Artificial Intelligence #Tech

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