Data Efficient Reinforcement Learning Professors in Global

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Yuhong Guo
Carleton University Canada
reinforcement learning
federated learning
representation learning
self-supervised learning
machine learning
continual learning
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Yuhong Guo
Carleton University Canada
reinforcement learning
federated learning
representation learning
self-supervised learning
machine learning
continual learning
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Nicholas Rhinehart
University of Toronto Canada
reinforcement learning
deep learning
robot learning
imitation learning
machine learning
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Pascal Poupart
University of Waterloo Canada
reinforcement learning
federated learning
self-supervised learning
machine learning
continual learning
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Kevin Luck
Vrije Universiteit Amsterdam Netherlands
deep reinforcement learning
reinforcement learning
deep learning
robot learning
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Florian Shkurti
University of Toronto Canada
reinforcement learning
inverse reinforcement learning
imitation learning
machine learning
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Mohsen Amiri
Stockholm University Sweden
reinforcement learning
deep learning
federated learning
machine learning
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Jason Lee
University of California, Berkeley United States of America
reinforcement learning
deep learning
representation learning
machine learning
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Jason Lee
University of California, Berkeley United States of America
reinforcement learning
deep learning
representation learning
machine learning
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Yaoliang Yu
University of Waterloo Canada
distributed learning
federated learning
representation learning
machine learning
robust stochastic optimization
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C. Green
University of Wisconsin–Madison United States of America
human learning
cognitive learning
depth learning
perceptual learning
motor learning
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Sophia Wilson
University of Copenhagen Denmark
data efficient machine learning
resource efficient machine learning
machine learning
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Colin Bellinger
University of Ottawa Canada
reinforcement learning
safe reinforcement learning
machine learning
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Pieter Abbeel
University of California, Berkeley United States of America
reinforcement learning
deep learning
imitation learning
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Wendelin Böhmer
Delft University of Technology Netherlands
reinforcement learning
multi-agent reinforcement learning
machine learning
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Ali Beikmohammadi
Stockholm University Sweden
reinforcement learning
deep learning
federated learning
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Kin-choong Yow
University of Regina Canada
deep reinforcement learning
deep learning
machine learning
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Silun Zhang
KTH Royal Institute of Technology Sweden
safe reinforcement learning
risk-averse reinforcement learning
incentive-driven algorithms
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Yangchen Pan
University of Oxford United Kingdom
reinforcement learning
deep learning
machine learning
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Sidney Givigi
Queen's University Canada
reinforcement learning
deep learning
machine learning
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Hongyang Dong
University of Warwick United Kingdom
reinforcement learning
deep learning
machine learning
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