Rule Learning Professors in Global

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C. Green
University of Wisconsin–Madison United States of America
human learning
motor learning
rate learning
cognitive learning
perceptual learning
transfer learning
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Yuhong Guo
Carleton University Canada
representation learning
reinforcement learning
machine learning
active learning
self-supervised learning
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Benedek Kurdi
University of Illinois United States of America
learning
reinforcement learning
causal learning
propositional learning
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Jason Lee
University of California, Berkeley United States of America
representation learning
reinforcement learning
machine learning
deep learning
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Tamara Van Gog
Utrecht University Netherlands
learning
example-based learning
self-regulated learning
multimedia learning
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Kurt Driessens
Maastricht University Netherlands
relational learning
reinforcement learning
transfer learning
machine learning
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Kurt Driessens
Maastricht University Netherlands
relational learning
reinforcement learning
transfer learning
machine learning
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Jason Lee
University of California, Berkeley United States of America
representation learning
reinforcement learning
machine learning
deep learning
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Kevin Luck
Vrije Universiteit Amsterdam Netherlands
robot learning
reinforcement learning
deep learning
deep reinforcement learning
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Pascal Vincent
University of Montreal Canada
representation learning
pattern recognition
machine learning
deep learning
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Maryam Fazel
University of Washington United States of America
learning control
reinforcement learning
machine learning
deep learning
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Pieter Abbeel
University of California, Berkeley United States of America
imitation learning
reinforcement learning
transfer learning
deep learning
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Alexander Rakhlin
Massachusetts Institute of Technology United States of America
statistical learning
reinforcement learning
machine learning
online learning
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Ferenc Huszár
University of Cambridge United Kingdom
representation learning
transfer learning
machine learning
deep learning
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Honglak Lee
University of Michigan United States of America
representation learning
large-scale learning
machine learning
deep learning
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Yichen Zhang
Purdue University United States of America
reinforcement learning
transfer learning
distributed learning
multi-task learning
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Kilian Weinberger
Cornell University Netherlands
metric learning
machine learning
deep learning
resource efficient learning
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Samory Kpotufe
Columbia University United States of America
adaptive learning
transfer learning
active learning
multi-task learning
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Oisin Mac Aodha
University of Edinburgh United Kingdom
machine teaching
machine learning
deep learning
active learning
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Kin-choong Yow
University of Regina Canada
pattern recognition
machine learning
deep learning
deep reinforcement learning
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Jessica Lee
University of Sydney Australia
rule learning
causal learning
associative learning
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