Asynchronous Learning Professors in Global

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Yuhong Guo
Carleton University Canada
self-supervised learning
continual learning
active learning
reinforcement learning
semi-supervised learning
machine learning
artificial intelligence
federated learning
representation learning
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Yuhong Guo
Carleton University Canada
self-supervised learning
continual learning
active learning
reinforcement learning
semi-supervised learning
machine learning
artificial intelligence
federated learning
representation learning
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Pascal Poupart
University of Waterloo Canada
self-supervised learning
continual learning
reinforcement learning
machine learning
federated learning
causal learning
shot learning
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C. Green
University of Wisconsin–Madison United States of America
human learning
motor learning
perceptual learning
cognitive learning
depth learning
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Nicholas Rhinehart
University of Toronto Canada
robot learning
imitation learning
reinforcement learning
machine learning
deep learning
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Maryam Fazel
University of Washington United States of America
reinforcement learning
machine learning
artificial intelligence
deep learning
learning control
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Linus Ericsson
University of Glasgow United Kingdom
automated machine learning
multi-modal learning
machine learning
artificial intelligence
representation learning
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Raymond Mooney
University of Texas at Austin United States of America
ensemble learning
active learning
semi-supervised learning
machine learning
statistical relational learning
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Honglak Lee
University of Michigan United States of America
large-scale learning
machine learning
artificial intelligence
deep learning
representation learning
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Joseph Gonzalez
University of California, Berkeley United States of America
asynchronous time series
accelerated deep learning
machine learning
federated learning
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Samory Kpotufe
Columbia University United States of America
adaptive learning
multi-task learning
active learning
statistical machine 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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Xujie Si
University of Toronto Canada
reinforcement learning
machine learning
artificial intelligence
deep learning
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Adam White
University of Alberta Canada
continual learning
reinforcement learning
machine learning
artificial intelligence
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Mengye Ren
New York University United States of America
continual learning
machine learning
artificial intelligence
representation learning
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Adam Shephard
University of Warwick United Kingdom
multi-modal learning
machine learning
artificial intelligence
deep learning
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Michael Ingrisch
Ludwig Maximilian University of Munich Germany
multimodal learning
machine learning
artificial intelligence
deep learning
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Christian Stöhr
Chalmers University of Technology Sweden
hybrid learning
digital learning
technology-enhanced learning
online learning
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Sidney Givigi
Queen's University Canada
reinforcement learning
machine learning
artificial intelligence
deep learning
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Yangchen Pan
University of Oxford United Kingdom
reinforcement learning
machine learning
artificial intelligence
deep learning
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Sophia Bello
University of Toronto Canada
active learning
language learning
experiential learning
artificial intelligence
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