Shot Learning Professors in Global

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Yuhong Guo
Carleton University Canada
few-shot learning
zero-shot learning
self-supervised learning
reinforcement learning
representation learning
semi-supervised learning
continual learning
active learning
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C. Green
University of Wisconsin–Madison United States of America
human learning
motor learning
rate learning
perceptual learning
cognitive learning
transfer learning
depth learning
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Rudolf Lioutikov
University of Texas at Austin United States of America
imitation learning
reinforcement learning
structure learning
skill acquisition
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Arthur Galamba
King's College London United Kingdom
hybrid learning
online learning
collaborative learning
stem learning
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Yichen Zhang
Purdue University United States of America
reinforcement learning
distributed learning
multi-task learning
transfer learning
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Samory Kpotufe
Columbia University United States of America
multi-task learning
transfer learning
adaptive learning
active learning
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Yinbei Li
Singapore Institute of Technology Singapore
robot learning
imitation learning
reinforcement learning
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Cheng Ouyang
University of Oxford United Kingdom
few-shot learning
zero-shot learning
multimodal learning
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Lina Yao
University of New South Wales Australia
few-shot learning
zero-shot learning
deep reinforcement learning
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Kevin Luck
Vrije Universiteit Amsterdam Netherlands
robot learning
reinforcement learning
deep reinforcement learning
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Benedek Kurdi
University of Illinois United States of America
learning
reinforcement learning
causal learning
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Alexander Rakhlin
Massachusetts Institute of Technology United States of America
statistical learning
reinforcement learning
online learning
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Il-min Kim
Queen's University Canada
few-shot learning
distributed learning
continual learning
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Tamara Van Gog
Utrecht University Netherlands
learning
multimedia learning
self-regulated learning
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Pieter Abbeel
University of California, Berkeley United States of America
imitation learning
reinforcement learning
transfer learning
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Piotr Koniusz
Australian National University Australia
few-shot learning
representation learning
graph learning
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Jessica Lee
University of Sydney Australia
rule learning
causal learning
associative learning
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Mengye Ren
New York University United States of America
few-shot learning
representation learning
continual learning
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Christian Stöhr
Chalmers University of Technology Sweden
digital learning
hybrid learning
online learning
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Florian Shkurti
University of Toronto Canada
imitation learning
reinforcement learning
inverse reinforcement learning
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Jan Vermunt
Eindhoven University of Technology Belgium
student learning
self-regulated learning
teacher learning
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